Signal processing: help tree improved 43/19943/7
Samuel GOUGEON [Sun, 8 Apr 2018 10:59:09 +0000 (12:59 +0200)]
 - miscellaneous dir removed (only 2 entries => root)
 - convol.xml moved to the dedicated subsection
 - intdec plot fixed. Image updated.:
 - untranslated files removed from non en_US directories
 - fr "Convolution" chapter name fixed

Change-Id: Ic985c1c658936ce4ca13ffe5e04e46cb1ea28fe8

82 files changed:
scilab/CHANGES.md
scilab/modules/helptools/etc/images_md5.txt
scilab/modules/helptools/images/intdec_1.png
scilab/modules/signal_processing/help/en_US/bilt.xml [moved from scilab/modules/signal_processing/help/en_US/miscellaneous/bilt.xml with 100% similarity]
scilab/modules/signal_processing/help/en_US/correlation_convolution/CHAPTER
scilab/modules/signal_processing/help/en_US/correlation_convolution/convol.xml [moved from scilab/modules/signal_processing/help/en_US/filters/convol.xml with 100% similarity]
scilab/modules/signal_processing/help/en_US/intdec.xml [moved from scilab/modules/signal_processing/help/en_US/spectral_estimation/intdec.xml with 64% similarity]
scilab/modules/signal_processing/help/en_US/miscellaneous/CHAPTER [deleted file]
scilab/modules/signal_processing/help/en_US/sincd.xml [moved from scilab/modules/signal_processing/help/en_US/miscellaneous/sincd.xml with 100% similarity]
scilab/modules/signal_processing/help/fr_FR/correlation_convolution/CHAPTER
scilab/modules/signal_processing/help/fr_FR/correlation_convolution/conv.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/correlation_convolution/conv2.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/correlation_convolution/convol2d.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/correlation_convolution/corr.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/correlation_convolution/hank.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/correlation_convolution/xcorr.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/CHAPTER
scilab/modules/signal_processing/help/fr_FR/filters/analpf.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/buttmag.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/cheb1mag.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/cheb2mag.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/convol.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/ell1mag.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/eqfir.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/eqiir.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/faurre.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/ffilt.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/filt_sinc.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/filter.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/find_freq.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/frmag.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/fsfirlin.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/group.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/hilbert.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/iirgroup.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/iirlp.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/kalm.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/lev.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/levin.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/lindquist.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/remez.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/remezb.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/srfaur.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/srkf.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/sskf.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/syredi.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/system.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/trans.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/wfir.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/wfir_gui.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/wiener.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/wigner.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/window.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/yulewalk.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/zpbutt.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/zpch1.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/zpch2.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/filters/zpell.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/howto/DesignEllipticFilter.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/identification/frfit.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/identification/lattn.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/identification/lattp.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/identification/mrfit.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/identification/phc.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/identification/rpem.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/miscellaneous/CHAPTER [deleted file]
scilab/modules/signal_processing/help/fr_FR/miscellaneous/bilt.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/miscellaneous/sincd.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/spectral_estimation/cepstrum.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/spectral_estimation/czt.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/spectral_estimation/intdec.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/spectral_estimation/mese.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/transforms/dct.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/transforms/dst.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/transforms/fft2.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/transforms/fftshift.xml [deleted file]
scilab/modules/signal_processing/help/fr_FR/transforms/hilb.xml [deleted file]
scilab/modules/signal_processing/help/ja_JP/bilt.xml [moved from scilab/modules/signal_processing/help/ja_JP/miscellaneous/bilt.xml with 100% similarity]
scilab/modules/signal_processing/help/ja_JP/correlation_convolution/convol.xml [moved from scilab/modules/signal_processing/help/ja_JP/filters/convol.xml with 100% similarity]
scilab/modules/signal_processing/help/ja_JP/intdec.xml [moved from scilab/modules/signal_processing/help/ja_JP/spectral_estimation/intdec.xml with 67% similarity]
scilab/modules/signal_processing/help/ja_JP/miscellaneous/CHAPTER [deleted file]
scilab/modules/signal_processing/help/ja_JP/sincd.xml [moved from scilab/modules/signal_processing/help/ja_JP/miscellaneous/sincd.xml with 100% similarity]

index 74714e8..96693b4 100644 (file)
@@ -249,7 +249,7 @@ Help pages:
   `printf`, `sprintf`, `iconvert`, `stdev`, `xlabel`, `and_op`, `or_op`, `permute`, `tree2code`, `%helps`,
   `scilab`, `flipdim`, `Matplot_properties`, `text_properties`, `meshgrid`, `ismatrix`, `xget`, `xset`, `ieee`, `evstr`,
   `uigetfont`, `uigetdir`, `uigetfile`, `uiputfile`, `cat`, `makecell`, `xstring`, `norm`, `barhomogenize`,
-  `colordef`, `matrix`, `coffg`, `diag`, `speye`, `sparse`, `recursionlimit`, `for`, `fileinfo`, `end`, `iconvert`, `Globalproperty`, `unique`
+  `colordef`, `matrix`, `coffg`, `diag`, `speye`, `sparse`, `recursionlimit`, `for`, `fileinfo`, `end`, `iconvert`, `Globalproperty`, `unique`, `intdec`
 * rewritten: `consolebox`, `double`, `isoview`, `pixel_drawing_mode`, `householder`, `or`, `|,||`,
  `and`, `&,&&`, `format`, `type`, `typeof`, `brackets`, `setlanguage`, `sleep`, `isinf`, `unique`,
  `bitor`, `bitxor`, `bitand`, `macr2tree`, `geomean`, `clf`, `getPreferencesValue`, `gcd`, `isglobal`,
@@ -262,6 +262,7 @@ Help pages:
   - CACSD and Signal Processing help pages have been sorted out.
   - Signal processing: new `Convolution - correlation` subsection. `wfir_gui`, `filt_sinc`, `hilb`, `fft2`, `fftshift`,
   `ifftshift`, `hilbert`, `cepstrum`, `conv`, `conv2`, `convol2d`, `xcor`, `corr`, `hank`, `mrfit`, `frfir` sorted out in existing subsections.
+  `bilt`, `convol`, `intdec`, and `sincd` moved.
   - Cells subsection created: `cell`, `cell2mat`, `cellstr`, `iscell`, `iscellstr`, `makecell`, `num2cell` gathered.
   - Colormaps and GUI/Menus subsections created
 * translations added:
index 5ec97f4..58f3f3a 100644 (file)
@@ -1057,7 +1057,7 @@ householder_1.png=8a7bce8cfadfbf5d70436734b66ec20d
 hsv2rgb_1.png=7d20c259e94301d9763fbddb7bff4784
 hsvcolormap_1.png=11918d88bcc793200af0b9f1b58b0554
 iir_1.png=e675c2755f68ddc4611c849895b63012
-intdec_1.png=9bf5d8f1a6aeddee68d7c5d831ef2d05
+intdec_1.png=d3d3cbde187a5f74a07b3d5611e66257
 interp1_1.png=e9a3f4319b2818ce4921b9bc3008d80
 interp2d_1.png=f4af61bc3faf493d778169ec7decc7ae
 interp2d_2.png=a62363849a3a9a3571dc1942fcebfbd3
index d3c7199..2ec1f3b 100644 (file)
Binary files a/scilab/modules/helptools/images/intdec_1.png and b/scilab/modules/helptools/images/intdec_1.png differ
     <refsection>
         <title>Examples</title>
         <programlisting role="example"><![CDATA[
-Fs1 = 10000;
-Fs2 = 14000;
-t1 = 0:1/Fs1:10;
-t2 = 0:1/Fs2:10;
-F0 = 500;
+Fs1 = 10000;               // initial sampling frequency
+Fs2 = 14000;               // targeted resampling frequency
+t1 = (0:1/Fs1:5)';
+t2 = (0:1/Fs2:5)';
+F0 = 2;                    // Signal frequency
 u1 = sin(2*%pi*F0*t1);
-u2 = sin(2*%pi*F0*t2);
-u2b = intdec(u1, Fs2/Fs1)
-plot(u2b, u2);
+u2 = sin(2*%pi*F0*t2);     // Direct sampling at targeted frequency (as reference)
+u2b = intdec(u1, Fs2/Fs1); // Resampled signal
+clf
+plot(t2,u2,"b", t2,(u2b-u2)*1000, "r");
+legend("Direct highly sampled u2","(resampled_u1 - u2) x 1000","in_upper_left");
  ]]></programlisting>
         <scilab:image>
-
-            Fs1 = 10000; Fs2 = 14000;
-            t1 = 0:1/Fs1:10; t2 = 0:1/Fs2:10;
-            F0 = 500;
-            u1 = sin(2*%pi*F0*t1); u2 = sin(2*%pi*F0*t2);
-            u2b = intdec(u1, Fs2/Fs1);
-            plot(u2b, u2);
+          Fs1 = 10000;               // initial sampling frequency
+          Fs2 = 14000;               // targeted resampling frequency
+          t1 = (0:1/Fs1:5)';
+          t2 = (0:1/Fs2:5)';
+          F0 = 2;                    // Signal frequency
+          u1 = sin(2*%pi*F0*t1);
+          u2 = sin(2*%pi*F0*t2);     // Direct sampling at targeted frequency (as reference)
+          u2b = intdec(u1, Fs2/Fs1); // Resampled signal
+          clf
+          plot(t2,u2,"b", t2,(u2b-u2)*1000, "r");
+          legend("Direct highly sampled u2","(resampled_u1 - u2) x 1000","in_upper_left");
         </scilab:image>
     </refsection>
 </refentry>
diff --git a/scilab/modules/signal_processing/help/en_US/miscellaneous/CHAPTER b/scilab/modules/signal_processing/help/en_US/miscellaneous/CHAPTER
deleted file mode 100644 (file)
index 0af0729..0000000
+++ /dev/null
@@ -1,2 +0,0 @@
-title = Miscellaneous
-
diff --git a/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/conv.xml b/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/conv.xml
deleted file mode 100644 (file)
index 1e1d32d..0000000
+++ /dev/null
@@ -1,140 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="en_US" xml:id="conv">
-    <refnamediv>
-        <refname>conv</refname>
-        <refpurpose>discrete 1-D convolution. </refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>C = conv(A,B [,shape])</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Parameters</title>
-        <variablelist>
-            <varlistentry>
-                <term>A</term>
-                <listitem>
-                    <para>
-                        a real or complex vector.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>B</term>
-                <listitem>
-                    <para>
-                        a real or complex vector.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>shape</term>
-                <listitem>
-                    <para>
-                        an optional character string with possible values:
-                    </para>
-                    <itemizedlist>
-                        <listitem>
-                            <literal>"full"</literal>, <literal>conv</literal>
-                            computes the full convolution. It is the
-                            default value.
-                        </listitem>
-                        <listitem>
-                            <literal>"same"</literal>, <literal>conv</literal>
-                            computes the central part of the convolution of the same
-                            size as <literal>A</literal>.
-                        </listitem>
-                        <listitem>
-                            <literal>"valid"</literal>, <literal>conv</literal>
-                            computes the convolution parts without the zero-padding
-                            of <literal>A</literal>.
-                        </listitem>
-                    </itemizedlist>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>C</term>
-                <listitem>
-                    <para>
-                        a real or complex vector.
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            <literal>conv</literal> uses a straightforward formal
-            implementation of the one-dimensional convolution equation in
-            spatial form.
-        </para>
-        <para>
-            <literal>C=conv(A,B [,shape])</literal> computes the
-            one-dimensional convolution of the vectors <literal>A</literal>
-            and <literal>B</literal>:
-        </para>
-        <itemizedlist>
-            <listitem>
-                With <literal>shape=="full"</literal> the
-                dimensions of the result<literal>C</literal> are given by
-                <literal>size(A,'*')+size(B,'*')+1</literal>. The indices of the
-                center element of <literal>B</literal> are defined as
-                <literal>floor((size(B,'*')+1)/2)</literal>.
-            </listitem>
-            <listitem>
-                With <literal>shape=="same"</literal> the
-                dimensions of the result<literal>C</literal> are given by
-                <literal>size(A)</literal>. The indices of the
-                center element of <literal>B</literal> are defined as
-                <literal>floor((size(B,'*')+1)/2)</literal>.
-            </listitem>
-            <listitem>
-                With <literal>shape=="valid"</literal> the dimensions
-                of the result <literal>C</literal> are given by
-                <literal>size(A,'*')-size(B,'*')+1)</literal> if
-                <literal>and(size(A,'*')-size(B,'*'))&gt;=0</literal> else
-                <literal>C</literal> is empty . The indices of the center
-                element of <literal>B</literal> are defined as
-                <literal>1</literal>.
-            </listitem>
-        </itemizedlist>
-        <para>
-            Note that <link linkend="convol">convol</link> can be more efficient for large arrays.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-        A=1:10;
-        B=[1 -1];
-        conv(A,B)
-    ]]></programlisting>
-    </refsection>
-    <refsection>
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="convol">convol</link>
-            </member>
-            <member>
-                <link linkend="conv2">conv2</link>
-            </member>
-        </simplelist>
-    </refsection>
-    <refsection>
-        <title>Used Functions</title>
-        <para>
-            The conv function is based on the  <link linkend="conv2">conv2</link> builtin.
-        </para>
-    </refsection>
-    <refsection>
-        <title>History</title>
-        <revhistory>
-            <revision>
-                <revnumber>5.4.0</revnumber>
-                <revremark>Function conv introduced.</revremark>
-            </revision>
-        </revhistory>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/conv2.xml b/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/conv2.xml
deleted file mode 100644 (file)
index 96830d8..0000000
+++ /dev/null
@@ -1,161 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="en_US" xml:id="conv2">
-    <refnamediv>
-        <refname>conv2</refname>
-        <refpurpose>discrete 2-D convolution. </refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>
-            C = conv2(A,B [,shape])
-            C = conv2(hrow,hcol,B [,shape])
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Parameters</title>
-        <variablelist>
-            <varlistentry>
-                <term>hrow</term>
-                <listitem>
-                    <para>
-                        a real or complex vector.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>hcol</term>
-                <listitem>
-                    <para>
-                        a real or complex vector.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>A</term>
-                <listitem>
-                    <para>
-                        a real or complex 2-D array.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>B</term>
-                <listitem>
-                    <para>
-                        a real or complex 2-D array.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>shape</term>
-                <listitem>
-                    <para>
-                        an optional character string with possible values:
-                    </para>
-                    <itemizedlist>
-                        <listitem>
-                            <literal>"full"</literal>, <literal>conv2</literal>
-                            computes the full two-dimensional convolution. It is the
-                            default value.
-                        </listitem>
-                        <listitem>
-                            <literal>"same"</literal>, <literal>conv2</literal>
-                            computes the central part of the convolution of the same
-                            size as <literal>A</literal>.
-                        </listitem>
-                        <listitem>
-                            <literal>"valid"</literal>, <literal>conv2</literal>
-                            computes the convolution parts without the zero-padding of <literal>A</literal>.
-                        </listitem>
-                    </itemizedlist>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>C</term>
-                <listitem>
-                    <para>
-                        a real or complex 2-D array.
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            <literal>conv2</literal> uses a straightforward formal
-            implementation of the two-dimensional convolution equation in
-            spatial form.
-        </para>
-        <para>
-            <literal>C=conv2(A,B [,shape])</literal> computes the
-            two-dimensional convolution of the arrays <literal>A</literal>
-            and <literal>B</literal>:
-        </para>
-        <itemizedlist><listitem>
-                With <literal>shape=="full"</literal> the
-                dimensions of the result<literal>C</literal> are given by
-                <literal>size(A)+size(B)+1</literal>. The indices of the
-                center element of <literal>B</literal> are defined as
-                <literal>floor((size(B)+1)/2)</literal>.
-            </listitem>
-            <listitem>
-                With <literal>shape=="same"</literal> the dimensions
-                of the result<literal>C</literal> are given by
-                <literal>size(A)</literal>. The indices of the center element of
-                <literal>B</literal> are defined as
-                <literal>floor((size(B)+1)/2)</literal>.
-            </listitem>
-            <listitem>
-                With <literal>shape=="valid"</literal> the dimensions
-                of the result <literal>C</literal> are given by
-                <literal>size(A)-size(B)+1)</literal> if
-                <literal>and(size(A)-size(B))&gt;=0</literal> else
-                <literal>C</literal> is empty . The indices of the center
-                element of <literal>B</literal> are defined as <literal>[1
-                    1]
-                </literal>
-                .
-            </listitem>
-        </itemizedlist>
-        <para>
-            The separable form <literal>C=conv2(hrow,hcol,B [,shape])</literal>is equivalent to <literal>C=conv2(hrow(:)*hcol(:).',B [,shape])</literal>
-        </para>
-        .
-        <para>
-            Note that <link linkend="convol2d">convol2d</link> can be more efficient for large arrays.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-    s = [1 2 1; 0 0 0; -1 -2 -1];//Sobel horizontal edge kernel
-    A = zeros(10,10);A(3:7,3:7) = 1;
-    conv2(s,A);
-
-    //separable form
-    u=[1;0;-1];v=[1 2 1];// u*v=s
-    conv2(u,v,A)
-    ]]></programlisting>
-    </refsection>
-    <refsection>
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="convol2d">convol2d</link>
-            </member>
-            <member>
-                <link linkend="conv">conv</link>
-            </member>
-        </simplelist>
-    </refsection>
-    <refsection>
-        <title>History</title>
-        <revhistory>
-            <revision>
-                <revnumber>5.4.0</revnumber>
-                <revremark>Function conv2 introduced.</revremark>
-            </revision>
-        </revhistory>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/convol2d.xml b/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/convol2d.xml
deleted file mode 100644 (file)
index eff6cac..0000000
+++ /dev/null
@@ -1,88 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<!--
- * Add some comments about XML file
--->
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="en_US" xml:id="convol2d">
-    <refnamediv>
-        <refname>convol2d</refname>
-        <refpurpose>discrete 2-D convolution, using fft. </refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>C = convol2d(A,B)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Parameters</title>
-        <variablelist>
-            <varlistentry>
-                <term>A</term>
-                <listitem>
-                    <para>
-                        a real or complex 2-D array.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>B</term>
-                <listitem>
-                    <para>
-                        a real or complex 2-D array.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>C</term>
-                <listitem>
-                    <para>
-                        a real or complex 2-D array.
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            <literal>convol2d</literal> uses fft to compute the full
-            two-dimensional discrete convolution. The
-            dimensions of the result<literal>C</literal> are given by
-            <literal>size(A)+size(B)+1</literal>. The indices of the
-            center element of <literal>B</literal> are defined as
-            <literal>floor((size(B)+1)/2)</literal>.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-    s = [1 2 1; 0 0 0; -1 -2 -1];//Sobel horizontal edge kernel
-    A = zeros(10,10);A(3:7,3:7) = 1;
-    convol2d(s,A);
-    ]]></programlisting>
-    </refsection>
-    <refsection>
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="conv2">conv2</link>
-            </member>
-            <member>
-                <link linkend="convol">convol</link>
-            </member>
-        </simplelist>
-    </refsection>
-    <refsection>
-        <title>Used Functions</title>
-        <para>
-            The  <literal>convol2d</literal> function is based on the <link linkend="fft">fft</link> builtin.
-        </para>
-    </refsection>
-    <refsection>
-        <title>History</title>
-        <revhistory>
-            <revision>
-                <revnumber>5.4.0</revnumber>
-                <revremark>Function convol2d introduced.</revremark>
-            </revision>
-        </revhistory>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/corr.xml b/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/corr.xml
deleted file mode 100644 (file)
index 9859a2f..0000000
+++ /dev/null
@@ -1,243 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="corr">
-    <refnamediv>
-        <refname>corr</refname>
-        <refpurpose>correlation, covariance</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[cov,Mean]=corr(x,[y],nlags)
-            [cov,Mean]=corr('fft',xmacro,[ymacro],n,sect)
-
-            [w,xu]=corr('updt',x1,[y1],w0)
-            [w,xu]=corr('updt',x2,[y2],w,xu)
-            ...
-            [wk]=corr('updt',xk,[yk],w,xu)
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>x</term>
-                <listitem>
-                    <para>a real vector</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>y</term>
-                <listitem>
-                    <para>a real vector, default value x.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>nlags</term>
-                <listitem>
-                    <para>integer, number of correlation coefficients desired.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>xmacro</term>
-                <listitem>
-                    <para>a scilab external (see below).</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>ymacro</term>
-                <listitem>
-                    <para>a scilab external (see below), default value xmacro</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>an integer, total size of the sequence (see below).</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>sect</term>
-                <listitem>
-                    <para>size of sections of the sequence (see below).</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>xi</term>
-                <listitem>
-                    <para>a real vector</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>yi</term>
-                <listitem>
-                    <para>a real vector,default value xi.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>cov</term>
-                <listitem>
-                    <para>real vector, the correlation coefficients</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>Mean</term>
-                <listitem>
-                    <para>real number or vector,  the mean of x and if given y</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Computes
-        </para>
-        <programlisting role=""><![CDATA[
-         n - m
-         ====
-         \                                       1
-cov(m) =  >   (x(k) - xmean) (y(m+k) - ymean) * ---
-         /                                       n
-         ====
-         k = 1
- ]]></programlisting>
-        <para>
-            for   m=0,..,<literal>nlag-1</literal> and two vectors <literal>x=[x(1),..,x(n)]</literal>
-            <literal>y=[y(1),..,y(n)]</literal>
-        </para>
-        <para>
-            Note that if x and y sequences are differents corr(x,y,...) is
-            different with corr(y,x,...)
-        </para>
-        <variablelist>
-            <varlistentry>
-                <term>Short sequences</term>
-                <listitem>
-                    <para>
-                        <literal>[cov,Mean]=corr(x,[y],nlags)</literal> returns the first nlags
-                        correlation coefficients and Mean = <literal>mean(x)</literal>
-                        (mean of <literal>[x,y]</literal> if <literal>y</literal> is an argument).
-                        The sequence <literal>x</literal> (resp. <literal>y</literal>) is assumed real, and <literal>x</literal>
-                        and <literal>y</literal> are of same dimension n.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>Long sequences</term>
-                <listitem>
-                    <para>
-                        <literal>[cov,Mean]=corr('fft',xmacro,[ymacro],n,sect)</literal> Here <literal>xmacro</literal> is either
-                    </para>
-                    <itemizedlist>
-                        <listitem>
-                            <para>
-                                a function of type <literal>[xx]=xmacro(sect,istart)</literal> which
-                                returns a vector <literal>xx</literal> of dimension
-                                <literal>nsect</literal> containing the part of the sequence with
-                                indices from <literal>istart</literal> to
-                                <literal>istart+sect-1</literal>.
-                            </para>
-                        </listitem>
-                        <listitem>
-                            <para>
-                                a fortran subroutine or C procedure which performs the same
-                                calculation. (See the source code of <literal>dgetx</literal> for an
-                                example). <literal>n</literal> = total size of the
-                                sequence. <literal>sect</literal> = size of sections of the
-                                sequence. <literal>sect</literal> must be a power of
-                                2. <literal>cov</literal> has dimension
-                                <literal>sect</literal>. Calculation is performed by FFT.
-                            </para>
-                        </listitem>
-                    </itemizedlist>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>Updating method</term>
-                <listitem>
-                    <programlisting role=""><![CDATA[
-[w,xu]=corr('updt',x1,[y1],w0)
-[w,xu]=corr('updt',x2,[y2],w,xu)
- ...
-wk=corr('updt',xk,[yk],w,xu)
- ]]></programlisting>
-                    <para>
-                        With this syntax the calculation is updated at each
-                        call to <literal>corr</literal>.
-                    </para>
-                    <programlisting role=""><![CDATA[
-w0 = 0*ones(1,2*nlags);
-nlags = power of 2.
- ]]></programlisting>
-                    <para>
-                        <literal>x1,x2,...</literal> are parts of <literal>x</literal> such that
-                        <literal>x=[x1,x2,...]</literal> and sizes of <literal>xi</literal> a power of
-                        2.  To get <literal>nlags</literal> coefficients a final fft must be
-                        performed <literal>c=fft(w,1)/n</literal>; <literal>cov=c(1nlags)</literal>
-                        (<literal>n</literal> is the size of <literal>x (y)</literal>).  Caution: this
-                        syntax assumes that <literal>xmean = ymean = 0</literal>.
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-x=%pi/10:%pi/10:102.4*%pi;
-rand('seed');rand('normal');
-y=[.8*sin(x)+.8*sin(2*x)+rand(x);.8*sin(x)+.8*sin(1.99*x)+rand(x)];
-c=[];
-for j=1:2,for k=1:2,c=[c;corr(y(k,:),y(j,:),64)];end;end;
-c=matrix(c,2,128);cov=[];
-for j=1:64,cov=[cov;c(:,(j-1)*2+1:2*j)];end;
-rand('unif')
-
-rand('normal');x=rand(1,256);y=-x;
-deff('[z]=xx(inc,is)','z=x(is:is+inc-1)');
-deff('[z]=yy(inc,is)','z=y(is:is+inc-1)');
-[c,mxy]=corr(x,y,32);
-x=x-mxy(1)*ones(x);y=y-mxy(2)*ones(y);  //centring
-c1=corr(x,y,32);c2=corr(x,32);
-norm(c1+c2,1)
-[c3,m3]=corr('fft',xx,yy,256,32);
-norm(c1-c3,1)
-[c4,m4]=corr('fft',xx,256,32);
-norm(m3,1),norm(m4,1)
-norm(c3-c1,1),norm(c4-c2,1)
-x1=x(1:128);x2=x(129:256);
-y1=y(1:128);y2=y(129:256);
-w0=0*ones(1:64);   //32 coeffs
-[w1,xu]=corr('u',x1,y1,w0);w2=corr('u',x2,y2,w1,xu);
-zz=real(fft(w2,1))/256;c5=zz(1:32);
-norm(c5-c1,1)
-[w1,xu]=corr('u',x1,w0);w2=corr('u',x2,w1,xu);
-zz=real(fft(w2,1))/256;c6=zz(1:32);
-norm(c6-c2,1)
-rand('unif')
-
-// test for Fortran or C external
-//
-deff('[y]=xmacro(sec,ist)','y=sin(ist:(ist+sec-1))');
-x=xmacro(100,1);
-[cc1,mm1]=corr(x,2^3);
-[cc,mm]=corr('fft',xmacro,100,2^3);
-[cc2,mm2]=corr('fft','corexx',100,2^3);
-[max(abs(cc-cc1)),max(abs(mm-mm1)),max(abs(cc-cc2)),max(abs(mm-mm2))]
-
-deff('[y]=ymacro(sec,ist)','y=cos(ist:(ist+sec-1))');
-y=ymacro(100,1);
-[cc1,mm1]=corr(x,y,2^3);
-[cc,mm]=corr('fft',xmacro,ymacro,100,2^3);
-[cc2,mm2]=corr('fft','corexx','corexy',100,2^3);
-[max(abs(cc-cc1)),max(abs(mm-mm1)),max(abs(cc-cc2)),max(abs(mm-mm2))]
- ]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="fft">fft</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/hank.xml b/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/hank.xml
deleted file mode 100644 (file)
index 6df98cd..0000000
+++ /dev/null
@@ -1,89 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns3="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:id="hank" xml:lang="fr">
-    <refnamediv>
-        <refname>hank</refname>
-        <refpurpose>covariance to hankel matrix</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>hk =hank(m, n, cov)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>m</term>
-                <listitem>
-                    <para>number of bloc-rows</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>number of bloc-columns</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>cov</term>
-                <listitem>
-                    <para>sequence of covariances; it must be given as :[R0 R1
-                        R2...Rk]
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>hk</term>
-                <listitem>
-                    <para>computed hankel matrix</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>This function builds the hankel matrix of size
-            <literal>(m*d,n*d)</literal> from the covariance sequence of a vector
-            process. More precisely:
-        </para>
-        <para>
-            This function builds the hankel matrix of size <literal>(m*d,n*d)</literal>
-            from the covariance sequence of a vector process. More precisely:
-        </para>
-        <para>
-            <latex><![CDATA[ \mathrm{hank}(m, n, [R_0, R_1, R_2, \ldots])=m\mbox{ blocks}\left\{\vphantom{\begin{matrix}R_0\cr R_1\cr R_2\cr\vdots\end{matrix}}\right.\left(\vphantom{\begin{matrix}R_0\cr R_1\cr R_2\cr\vdots\end{matrix}}\right.\overbrace{\begin{matrix}R_0 & R_1 & R_2 & \cdots\cr R_1 & R_2 & \cdots &\cr R_2 & \cdots &&\cr \vdots&&&\cr\end{matrix}}^{n \mbox{ blocks}}\left.\vphantom{\begin{matrix}R_0\cr R_1\cr R_2\cr\vdots\end{matrix}}\right) ]]></latex>
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example">//Example of how to use the hank macro for
-            //building a Hankel matrix from multidimensional
-            //data (covariance or Markov parameters e.g.)
-            //
-            //This is used e.g. in the solution of normal equations
-            //by classical identification methods (Instrumental Variables e.g.)
-            //
-            //1)let's generate the multidimensional data under the form :
-            //  C=[c_0 c_1 c_2 .... c_n]
-            //where each bloc c_k is a d-dimensional matrix (e.g. the k-th correlation
-            //of a d-dimensional stochastic process X(t) [c_k = E(X(t) X'(t+k)], '
-            //being the transposition in scilab)
-            //
-            //we take here d=2 and n=64
-
-            c = rand(2, 2 * 64)
-
-            //generate the hankel matrix H (with 4 bloc-rows and 5 bloc-columns)
-            //from the data in c
-
-            H = hank(4, 5, c);
-        </programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="toeplitz">toeplitz</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/xcorr.xml b/scilab/modules/signal_processing/help/fr_FR/correlation_convolution/xcorr.xml
deleted file mode 100644 (file)
index da562a0..0000000
+++ /dev/null
@@ -1,247 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<!--
-This file is part Scilab
-Copyright (C) 2012 - INRIA - Serge Steer
-Copyright (C) 2012 - 2016 - Scilab Enterprises
-
-This file is hereby licensed under the terms of the GNU GPL v2.0,
-pursuant to article 5.3.4 of the CeCILL v.2.1.
-This file was originally licensed under the terms of the CeCILL v2.1,
-and continues to be available under such terms.
-For more information, see the COPYING file which you should have received
-along with this program.
--->
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns3="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:id="xcorr" xml:lang="fr">
-    <refnamediv>
-        <refname>xcorr</refname>
-        <refpurpose>Computes discrete auto or cross correlation</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[c [,lagindex]] = xcorr(x [,maxlags [,scaling]])
-            [c [,lagindex]] = xcorr(x,y [,maxlags [,scaling]])
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Parameters</title>
-        <variablelist>
-            <varlistentry>
-                <term>x</term>
-                <listitem>
-                    <para>a vector of real or complex floating point numbers.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>y</term>
-                <listitem>
-                    <para>a vector of real or complex floating point numbers. The
-                        default value is <literal>x</literal>.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>maxlags</term>
-                <listitem>
-                    <para>a scalar with integer value greater than 1. The default value
-                        is <literal>n</literal>. Where <literal>n</literal> is the maximum
-                        of the <literal>x</literal> and <literal>y</literal> vector
-                        length.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>scaling</term>
-                <listitem>
-                    <para>a character string with possible value:
-                        <literal>"biased"</literal>, <literal>"unbiased"</literal>,
-                        <literal>"coeff"</literal>, <literal>"none"</literal>. The default
-                        value is <literal>"none"</literal>.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>c</term>
-                <listitem>
-                    <para>a vector of real or complex floating point numbers with same
-                        orientation as <literal>x</literal>.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>lagindex</term>
-                <listitem>
-                    <para>a row vector, containing the lags index corresponding to the
-                        <literal>c</literal> values.
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <itemizedlist>
-            <listitem>
-                <literal>c=xcorr(x)</literal>
-
-                computes the un-normalized discrete auto correlation:
-
-                <latex>{\begin{matrix}C_k = \sum_{i=1}^{n-k}
-                    {x_{i+k}*x^{*}_i}, k \geq 0 \\ C_k = C^{*}_{-k}, k \leq
-                    -1\end{matrix}.$
-                </latex>
-
-                and return in
-
-                <literal>c</literal>
-
-                the sequence of auto correlation lags
-
-                <latex>$C_k,k=-n:n$</latex>
-
-                with
-
-                <literal>n</literal>
-
-                is the length of
-
-                <literal>x</literal>
-
-
-            </listitem>
-            <listitem>
-                <literal>xcorr(x,y)</literal>
-
-                computes the un-normalized discrete cross correlation:
-
-                <latex>{\begin{matrix}C_k = \sum_{i=1}^{n-k}
-                    {x_{i+k}*y^{*}_i}, k \geq 0 \\ C_k = C^{*}_{-k}, k \leq
-                    -1\end{matrix}}.$
-                </latex>
-
-                and return in
-
-                <literal>c</literal>
-
-                the sequence of auto correlation lags
-
-                <latex>$C_k,k=-n:n$</latex>
-
-                with
-
-                <literal>n</literal>
-
-                is the maximum of
-
-                <literal>x</literal>
-
-                and
-
-                <literal>y</literal>
-
-                length's.
-            </listitem>
-        </itemizedlist>
-        <para>
-            If the <literal>maxlags</literal> argument is given
-            <literal>xcorr</literal> returns in <literal>c</literal> the sequence of
-            auto correlation lags <latex>$C_k,k=-maxlags:maxlags$</latex>. If
-            <literal>maxlags</literal> is greater than <literal>length(x)</literal>,
-            the first and last values of <literal>c</literal> are zero.
-        </para>
-        <para>
-            The <literal>scaling</literal> argument describes how
-            <latex>C(k)</latex> is normalized before being returned in
-            <literal>c</literal>:
-            <itemizedlist>
-                <listitem>
-                    <term>"biased"</term>:<literal>c=</literal><latex>$C$</latex><literal>/n</literal>.
-                </listitem>
-                <listitem>
-                    <term>"unbiased"</term>:<literal>c=</literal><latex>$C$</latex><literal>./(n-(-maxlags:maxlags))</literal>.
-                </listitem>
-                <listitem>
-                    <term>"coeff"</term>:<literal>c=</literal><latex>$C$</latex><literal>/(norm(x)*norm(y))</literal>.
-                </listitem>
-            </itemizedlist>
-        </para>
-    </refsection>
-    <refsection>
-        <title>Remark</title>
-
-        The
-
-        <link linkend="corr">corr</link>
-
-        function computes the "biased" covariance of
-
-        <literal>x</literal>
-
-        and
-
-        <literal>y</literal>
-
-        and only return in
-
-        <literal>c</literal>
-
-        the sequence of auto correlation lags
-
-        <latex>$C_k,k \geq 0$</latex>
-
-        .
-    </refsection>
-    <refsection>
-        <refsection>
-            <title>Method</title> This function computes
-            <latex>$C$</latex> using
-            <literal>ifft(fft(x).*conj(fft(y)))</literal>.
-        </refsection>
-        <refsection>
-            <title>Examples</title>
-            <programlisting role="example">t = linspace(0, 100, 2000);
-                y = 0.8 * sin(t) + 0.8 * sin(2 * t);
-                [c, ind] = xcorr(y, "biased");
-                plot(ind, c)
-            </programlisting>
-            <scilab:image>
-                t = linspace(0, 100, 2000);
-                y = 0.8 * sin(t) + 0.8 * sin(2 * t);
-                [c, ind] = xcorr(y, "biased");
-                plot(ind, c)
-            </scilab:image>
-        </refsection>
-        <refsection>
-            <title>See also</title>
-            <simplelist type="inline">
-                <member>
-                    <link linkend="xcov">xcov</link>
-                </member>
-                <member>
-                    <link linkend="corr">corr</link>
-                </member>
-                <member>
-                    <link linkend="fft">fft</link>
-                </member>
-            </simplelist>
-        </refsection>
-        <refsection>
-            <title>Authors</title>
-            <simplelist type="vert">
-                <member>Serge Steer, INRIA</member>
-            </simplelist>
-        </refsection>
-        <title>Used Functions</title>
-        <para>
-            <link linkend="fft">fft</link>
-        </para>
-    </refsection>
-    <refsection>
-        <title>History</title>
-        <revhistory>
-            <revision>
-                <revnumber>5.4.0</revnumber>
-                <revremark>xcorr added.</revremark>
-            </revision>
-        </revhistory>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/analpf.xml b/scilab/modules/signal_processing/help/fr_FR/filters/analpf.xml
deleted file mode 100644 (file)
index 9f719bf..0000000
+++ /dev/null
@@ -1,220 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook"  xml:lang="fr" xmlns:scilab="http://www.scilab.org" xml:id="analpf">
-    <refnamediv>
-        <refname>analpf</refname>
-        <refpurpose>create analog low-pass filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>
-            [hs,pols,zers,gain]=analpf(n,fdesign,rp,omega)
-            hs=analpf(n,fdesign,rp,omega)
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>positive integer: filter order</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fdesign</term>
-                <listitem>
-                    <para>a string: that indicated the filter design method: </para>
-                    <itemizedlist mark="bullet">
-                        <listitem>
-                            <para>"butt" is for  Butterworth filter.</para>
-                        </listitem>
-                        <listitem>
-                            <para>"cheb1" is for Chebyshev type I filter.</para>
-                        </listitem>
-                        <listitem>
-                            <para>"cheb2" is for Chebyshev type II filter (also called inverse  Chebyshev filter).</para>
-                        </listitem>
-                        <listitem>
-                            <para>"ellip" is for  elliptic filter.</para>
-                        </listitem>
-                    </itemizedlist>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>rp</term>
-                <listitem>
-                    <para>a 2-vector of ripples values for "cheb1", "cheb2" and
-                        "ellip" filters. It's elements value must respect
-                        <literal>0&lt;rp(1),rp(2)&lt;1</literal>.
-                    </para>
-                    <itemizedlist mark="bullet">
-                        <listitem>
-                            <para>
-                                For "cheb1" filters only <literal>rp(1)</literal>
-                                is used. The passband ripple is between
-                                <literal>1-rp(1)</literal> and <literal>1</literal>.
-                            </para>
-                        </listitem>
-                        <listitem>
-                            <para>
-                                For "cheb2" filters only <literal>rp(2)</literal>
-                                is used. The stopband ripple is between
-                                <literal>0</literal> and
-                                <literal>rp(2)</literal>.
-                            </para>
-                        </listitem>
-                        <listitem>
-                            <para>
-                                For "ellip" filters <literal>rp(1)</literal> and
-                                <literal>rp(2)</literal> are both used.  The passband
-                                ripple is between <literal>1-rp(1)</literal> and
-                                <literal>1</literal> while the stopband ripple is
-                                between <literal>0</literal> and
-                                <literal>rp(2)</literal>.
-                            </para>
-                        </listitem>
-                    </itemizedlist>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>omega</term>
-                <listitem>
-                    <para>cut-off frequency of low-pass filter in rad/s</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>hs</term>
-                <listitem>
-                    <para>
-                        the rational polynomial transfer function (see <link linkend="syslin">syslin</link>). Is is
-                        <literal>hs = gain*syslin("c", real(poly(zers, "s")), real(poly(pols, "s")))
-                        </literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>pols</term>
-                <listitem>
-                    <para>a row vector: the poles of transfer function</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zers</term>
-                <listitem>
-                    <para>a row vector: zeros of transfer function</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>gain</term>
-                <listitem>
-                    <para>a scalar: the gain of transfer function</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            This Creates analog low-pass filter with cut-off pulsation at
-            omega. It is a driver over the <link linkend="zpbutt">zpbutt</link>, <link linkend="zpch1">zpch1</link>, <link linkend="zpch2">zpch2</link>
-            and <link linkend="zpell">zpell</link> functions.
-        </para>
-        <para>
-            The Butterworth filter has no ripples in the passband and slowly
-            rolls off towards zero in the stopband.  Butterworth filters
-            have a monotonically changing magnitude function with omega,
-            unlike other filter types that have non-monotonic ripple in the
-            passband and/or the stopband.  Butterworth filters have a more
-            linear phase response in the pass-band than the others.
-        </para>
-        <para>
-            Chebyshev filters have a steeper roll-off and more passband ripple
-            (type I) or stopband ripple (type II) than Butterworth
-            filters. Chebyshev filters have the property that they minimize
-            the error between the idealized and the actual filter
-            characteristic over the range of the filter, but with ripples in
-            the passband.
-        </para>
-        <para>
-            Elliptic filter have equalized ripple behavior in both the
-            passband and the stopband. The amount of ripple in each band is
-            independently adjustable, and no other filter of equal order can
-            have a faster transition in gain between the passband and the
-            stopband, for the given values of ripple.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-// Evaluate magnitude response of the filter
-fcut = 5; //hz
-n = 7; // Filter order
-hc1 = analpf(n, 'cheb1', [0.1 0], fcut*2*%pi);
-hc2 = analpf(n, 'cheb2', [0 0.1], fcut*2*%pi);
-he = analpf(n, 'ellip', [0.1 0.1], fcut*2*%pi);
-hb = analpf(n, 'butt', [0 0], fcut*2*%pi);
-hc1.dt = 'c';
-hc2.dt = 'c';
-he.dt = 'c';
-hb.dt = 'c';
-clf();
-[fr, hf] = repfreq(hc1, 0, 15);
-plot(fr, abs(hf), 'b')
-[fr, hf] = repfreq(hc2, 0, 15);
-plot(fr,abs(hf),'g')
-[fr, hf] = repfreq(he, 0, 15);
-plot(fr,abs(hf),'r')
-[fr, hf] = repfreq(hb, 0, 15);
-plot(fr, abs(hf), 'c')
-
-legend(["Chebyshev I", "Chebyshev II", "Elliptic", "Butterworth"]);
-xgrid()
-xlabel("Frequency (Hz)")
-ylabel("Gain")
-title("Analog filters of order 7")
- ]]></programlisting>
-        <para>
-            <scilab:image>
-                fcut=5; //hz
-                n=7;//filter order
-                hc1=analpf(n,'cheb1',[0.1 0],fcut*2*%pi);
-                hc2=analpf(n,'cheb2',[0 0.1],fcut*2*%pi);
-                he=analpf(n,'ellip',[0.1 0.1],fcut*2*%pi);
-                hb=analpf(n,'butt',[0 0],fcut*2*%pi);
-                hc1.dt='c';hc2.dt='c';he.dt='c';hb.dt='c';
-                clf();
-                [fr, hf]=repfreq(hc1,0,15);
-                plot(fr,abs(hf),'b')
-                [fr, hf]=repfreq(hc2,0,15);
-                plot(fr,abs(hf),'g')
-                [fr, hf]=repfreq(he,0,15);
-                plot(fr,abs(hf),'r')
-                [fr, hf]=repfreq(hb,0,15);
-                plot(fr,abs(hf),'c')
-
-                legend(["Chebyshev I","Chebyshev II","Elliptic","Butterworth"]);
-                xgrid()
-                xlabel("Frequency (Hz)")
-                ylabel("Gain")
-                title("Analog filters of order 7")
-            </scilab:image>
-        </para>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="repfreq">repfreq</link>
-            </member>
-            <member>
-                <link linkend="bode">bode</link>
-            </member>
-            <member>
-                <link linkend="csim">csim</link>
-            </member>
-            <member>
-                <link linkend="syslin">syslin</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/buttmag.xml b/scilab/modules/signal_processing/help/fr_FR/filters/buttmag.xml
deleted file mode 100644 (file)
index 68906a3..0000000
+++ /dev/null
@@ -1,61 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="buttmag">
-    <refnamediv>
-        <refname>buttmag</refname>
-        <refpurpose>Power transmission of a Butterworth filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[h]=buttmag(order,omegac,sample)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>order</term>
-                <listitem>
-                    <para>integer : filter order</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>omegac</term>
-                <listitem>
-                    <para>real : cut-off angular frequency (in rad/s)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>sample</term>
-                <listitem>
-                    <para>real vector of angular frequencies (in rad/s), where the transmission must be evaluated.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>h</term>
-                <listitem>
-                    <para>Butterworth filter values at sample points</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            squared magnitude response of a Butterworth filter
-            <literal>omegac</literal> = cutoff frequency ; <literal>sample</literal> = sample of frequencies
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-//squared magnitude response of Butterworth filter
-h=buttmag(13,300,1:1000);
-mag=20*log(h)'/log(10);
-plot2d((1:1000)',mag,[2],"011"," ",[0,-180,1000,20])
- ]]></programlisting>
-        <scilab:image><![CDATA[
-h=buttmag(13,300,1:1000);
-mag=20*log(h)'/log(10);
-plot2d((1:1000)',mag,[2],"011"," ",[0,-180,1000,20])
-]]>     </scilab:image>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/cheb1mag.xml b/scilab/modules/signal_processing/help/fr_FR/filters/cheb1mag.xml
deleted file mode 100644 (file)
index a8a1073..0000000
+++ /dev/null
@@ -1,88 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="cheb1mag">
-    <refnamediv>
-        <refname>cheb1mag</refname>
-        <refpurpose>response of Chebyshev type 1 filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[h2]=cheb1mag(n,omegac,epsilon,sample)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>integer : filter order</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>omegac</term>
-                <listitem>
-                    <para>real : cut-off frequency</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>epsilon</term>
-                <listitem>
-                    <para>real : ripple in pass band</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>sample</term>
-                <listitem>
-                    <para>
-                        vector of frequencies where <literal>cheb1mag</literal> is evaluated
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>h2</term>
-                <listitem>
-                    <para>Chebyshev I filter values at sample points</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Square magnitude response of a type 1 Chebyshev filter.
-        </para>
-        <para>
-            <literal>omegac</literal>=passband edge.
-        </para>
-        <para>
-            <literal>epsilon</literal>such that <literal>1/(1+epsilon^2)</literal>=passband ripple.
-        </para>
-        <para>
-            <literal>sample</literal>vector of frequencies where the square magnitude
-            is desired.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-//Chebyshev; ripple in the passband
-n=13;epsilon=0.2;omegac=3;samples=0:0.05:10;
-h=cheb1mag(n,omegac,epsilon,samples);
-plot2d(samples,h)
-xtitle('','frequencies','magnitude')
- ]]></programlisting>
-        <scilab:image><![CDATA[
-n=13;epsilon=0.2;omegac=3;samples=0:0.05:10;
-h=cheb1mag(n,omegac,epsilon,samples);
-plot2d(samples,h)
-xtitle('','frequencies','magnitude')
-]]>     </scilab:image>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="buttmag">buttmag</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/cheb2mag.xml b/scilab/modules/signal_processing/help/fr_FR/filters/cheb2mag.xml
deleted file mode 100644 (file)
index 9e7afd3..0000000
+++ /dev/null
@@ -1,97 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="cheb2mag">
-    <refnamediv>
-        <refname>cheb2mag</refname>
-        <refpurpose>response of type 2 Chebyshev filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[h2]=cheb2mag(n,omegar,A,sample)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>integer ; filter order</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>omegar</term>
-                <listitem>
-                    <para>real scalar : cut-off frequency</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>A</term>
-                <listitem>
-                    <para>attenuation in stop band</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>sample</term>
-                <listitem>
-                    <para>vector of frequencies where cheb2mag is evaluated</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>h2</term>
-                <listitem>
-                    <para>vector of Chebyshev II filter values at sample points</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Square magnitude response of a type 2 Chebyshev filter.
-        </para>
-        <para>
-            <literal>omegar</literal> = stopband edge, <literal>sample</literal> = vector of
-            frequencies where the square magnitude <literal>h2</literal> is desired.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-//Chebyshev; ripple in the stopband
-n=10;
-omegar=6;
-A=1/0.2;
-Samples=0.0001:0.05:10;
-h2=cheb2mag(n,omegar,A,Samples);
-plot(Samples,log(h2)/log(10))
-xtitle("", "frequencies", "magnitude in dB");
-
-//Plotting of frequency edges
-minval=(-max(-log(h2)))/log(10);
-plot2d([omegar;omegar],[minval;0],[2],"000");
-
-//Computation of the attenuation in dB at the stopband edge
-attenuation=-log(A*A)/log(10);
-plot2d(Samples',attenuation*ones(Samples)',[5],"000")
- ]]></programlisting>
-        <scilab:image><![CDATA[
-n=10;omegar=6;A=1/0.2;Samples=0.0001:0.05:10;
-h2=cheb2mag(n,omegar,A,Samples);
-plot(Samples,log(h2)/log(10))
-xtitle("", "frequencies", "magnitude in dB");
-
-minval=(-max(-log(h2)))/log(10);
-plot2d([omegar;omegar],[minval;0],[2],"000");
-
-attenuation=-log(A*A)/log(10);
-plot2d(Samples',attenuation*ones(Samples)',[5],"000")
-]]>     </scilab:image>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="cheb1mag">cheb1mag</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/convol.xml b/scilab/modules/signal_processing/help/fr_FR/filters/convol.xml
deleted file mode 100644 (file)
index ddb5c20..0000000
+++ /dev/null
@@ -1,144 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns3="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:id="convol" xml:lang="fr">
-    <refnamediv>
-        <refname>convol</refname>
-        <refpurpose>convolution</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>
-            [y]=convol(h,x)
-            [y,e1]=convol(h,x,e0)
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>h</term>
-                <listitem>
-                    <para>a vector, first input sequence ("short" one) </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x</term>
-                <listitem>
-                    <para>a vector, second input sequence ( "long" one)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>e0</term>
-                <listitem>
-                    <para>a vector,old tail to overlap add (not used in first
-                        call)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>y</term>
-                <listitem>
-                    <para>a vector, the convolution. </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>e1</term>
-                <listitem>
-                    <para>new tail to overlap add (not used in last call)</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Calculates the convolution <literal>y= h*x</literal> of two discrete
-            sequences by using the fft. The convolution is defined as follows:
-        </para>
-        <para>
-            <inlinemediaobject>
-                <imageobject>
-                    <imagedata>
-                        <mml:math>
-                            <mml:semantics>
-                                <mml:mrow>
-                                    <mml:msub>
-                                        <mml:mi>y</mml:mi>
-                                        <mml:mi>k</mml:mi>
-                                    </mml:msub>
-                                    <mml:mo mml:stretchy="false">=</mml:mo>
-                                    <mml:mrow>
-                                        <mml:mrow>
-                                            <mml:msub>
-                                                <mml:mo mml:stretchy="false">∑</mml:mo>
-                                                <mml:mi>j</mml:mi>
-                                            </mml:msub>
-                                            <mml:msub>
-                                                <mml:mi>h</mml:mi>
-                                                <mml:mi>j</mml:mi>
-                                            </mml:msub>
-                                        </mml:mrow>
-                                        <mml:mo mml:stretchy="false">∗</mml:mo>
-                                        <mml:msub>
-                                            <mml:mi>x</mml:mi>
-                                            <mml:mrow>
-                                                <mml:mrow>
-                                                    <mml:mi>k</mml:mi>
-                                                    <mml:mo mml:stretchy="false">+</mml:mo>
-                                                    <mml:mn>1</mml:mn>
-                                                </mml:mrow>
-                                                <mml:mo mml:stretchy="false">−</mml:mo>
-                                                <mml:mi>j</mml:mi>
-                                            </mml:mrow>
-                                        </mml:msub>
-                                    </mml:mrow>
-                                </mml:mrow>
-                                <mml:annotation mml:encoding="StarMath 5.0">y_k=sum_j h_j*x_{k+1-j}
-                                </mml:annotation>
-                            </mml:semantics>
-                        </mml:math>
-                    </imagedata>
-                </imageobject>
-            </inlinemediaobject>
-        </para>
-        <para>Overlap add method can be used.</para>
-        <para>USE OF OVERLAP ADD METHOD: For
-            <literal>x=[x1,x2,...,xNm1,xN]</literal> First call is
-            <literal>[y1,e1]=convol(h,x1);</literal> Subsequent calls :
-            <literal>[yk,ek]=convol(h,xk,ekm1)</literal>; Final call :
-            <literal>[yN]=convol(h,xN,eNm1);</literal> Finally
-            <literal>y=[y1,y2,...,yNm1,yN]</literal>.
-        </para>
-        <para>The algorithm based on the convolution definition is
-            implemented for polynomial
-            product: <literal>y=convol(h,x)</literal> is equivalent
-            to <literal>y=coeff(poly(h,'z','c')*poly(x,'z','c')</literal> but
-            much more efficient if <literal>x</literal> is a "long" array.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-x=1:3;
-h1=[1,0,0,0,0];h2=[0,1,0,0,0];h3=[0,0,1,0,0];
-x1=convol(h1,x),x2=convol(h2,x),x3=convol(h3,x),
-convol(h1+h2+h3,x)
-p1=poly(x,'x','coeff')
-p2=poly(h1+h2+h3,'x','coeff')
-p1*p2
- ]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="corr">corr</link>
-            </member>
-            <member>
-                <link linkend="fft">fft</link>
-            </member>
-            <member>
-                <link linkend="pspect">pspect</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/ell1mag.xml b/scilab/modules/signal_processing/help/fr_FR/filters/ell1mag.xml
deleted file mode 100644 (file)
index 0651bbf..0000000
+++ /dev/null
@@ -1,93 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="ell1mag">
-    <refnamediv>
-        <refname>ell1mag</refname>
-        <refpurpose>magnitude of elliptic filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[v]=ell1mag(eps,m1,z)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>eps</term>
-                <listitem>
-                    <para>
-                        passband ripple=<literal>1/(1+eps^2)</literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>m1</term>
-                <listitem>
-                    <para>
-                        stopband ripple=<literal>1/(1+(eps^2)/m1)</literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>z</term>
-                <listitem>
-                    <para>sample vector of values in the complex plane</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>v</term>
-                <listitem>
-                    <para>elliptic filter values at sample points</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Function used for squared magnitude of an elliptic filter.
-            Usually <literal>m1=eps*eps/(a*a-1)</literal>. Returns
-            <literal>v=real(ones(z)./(ones(z)+eps*eps*s.*s))</literal> for <literal>s=%sn(z,m1)</literal>.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-deff('[alpha,BeTa]=alpha_beta(n,m,m1)',...
-'if 2*int(n/2)==n then, BeTa=K1; else, BeTa=0;end;'+...
-'alpha=%k(1-m1)/%k(1-m);')
-epsilon=0.1;A=10;  //ripple parameters
-m1=(epsilon*epsilon)/(A*A-1);n=5;omegac=6;
-m=find_freq(epsilon,A,n);omegar = omegac/sqrt(m)
-%k(1-m1)*%k(m)/(%k(m1)*%k(1-m))-n   //Check...
-[alpha,Beta]=alpha_beta(n,m,m1)
-alpha*delip(1,sqrt(m))-n*%k(m1)      //Check
-samples=0:0.01:20;
-//Now we map the positive real axis into the contour...
-z=alpha*delip(samples/omegac,sqrt(m))+Beta*ones(samples);
-plot(samples,ell1mag(epsilon,m1,z))
- ]]></programlisting>
-        <scilab:image><![CDATA[
-deff('[alpha,BeTa]=alpha_beta(n,m,m1)',...
-'if 2*int(n/2)==n then, BeTa=K1; else, BeTa=0;end;'+...
-'alpha=%k(1-m1)/%k(1-m);')
-epsilon=0.1;A=10;  //ripple parameters
-m1=(epsilon*epsilon)/(A*A-1);n=5;omegac=6;
-m=find_freq(epsilon,A,n);omegar = omegac/sqrt(m)
-%k(1-m1)*%k(m)/(%k(m1)*%k(1-m))-n   //Check...
-[alpha,Beta]=alpha_beta(n,m,m1)
-alpha*delip(1,sqrt(m))-n*%k(m1)      //Check
-samples=0:0.01:20;
-//Now we map the positive real axis into the contour...
-z=alpha*delip(samples/omegac,sqrt(m))+Beta*ones(samples);
-plot(samples,ell1mag(epsilon,m1,z))
-]]>     </scilab:image>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="buttmag">buttmag</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/eqfir.xml b/scilab/modules/signal_processing/help/fr_FR/filters/eqfir.xml
deleted file mode 100644 (file)
index 3f65c68..0000000
+++ /dev/null
@@ -1,65 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="eqfir">
-    <refnamediv>
-        <refname>eqfir</refname>
-        <refpurpose>minimax approximation of FIR filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[hn]=eqfir(nf,bedge,des,wate)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>nf</term>
-                <listitem>
-                    <para>number of output filter points desired</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>bedge</term>
-                <listitem>
-                    <para>Mx2 matrix giving a pair of edges for each band</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>des</term>
-                <listitem>
-                    <para>M-vector giving desired magnitude for each band</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>wate</term>
-                <listitem>
-                    <para>M-vector giving relative weight of error in each band</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>hn</term>
-                <listitem>
-                    <para>output of linear-phase FIR filter coefficients</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Minimax approximation of multi-band, linear phase, FIR filter
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-hn=eqfir(33,[0 .2;.25 .35;.4 .5],[0 1 0],[1 1 1]);
-[hm,fr]=frmag(hn,256);
-plot(fr,hm),
- ]]></programlisting>
-        <scilab:image><![CDATA[
-hn=eqfir(33,[0 .2;.25 .35;.4 .5],[0 1 0],[1 1 1]);
-[hm,fr]=frmag(hn,256);
-plot(fr,hm),
-]]>     </scilab:image>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/eqiir.xml b/scilab/modules/signal_processing/help/fr_FR/filters/eqiir.xml
deleted file mode 100644 (file)
index 7af9647..0000000
+++ /dev/null
@@ -1,123 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns4="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:id="eqiir" xml:lang="fr">
-    <refnamediv>
-        <refname>eqiir</refname>
-        <refpurpose>Design of iir filters</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[cells,fact,zzeros,zpoles]=eqiir(ftype,approx,om,deltap,deltas)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>ftype</term>
-                <listitem>
-                    <para>
-                        filter type (<literal>'lp','hp','sb','bp'</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>approx</term>
-                <listitem>
-                    <para>design approximation
-                        (<literal>'butt','cheb1','cheb2','ellip'</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>om</term>
-                <listitem>
-                    <para>4-vector of cutoff frequencies (in radians)
-                        <literal>om=[om1,om2,om3,om4]</literal>, <literal>0 &lt;= om1 &lt;=
-                            om2 &lt;= om3 &lt;= om4 &lt;= pi
-                        </literal>
-                        .When
-                        <literal>ftype</literal>='lp' or 'hp', <literal>om3</literal> and
-                        <literal>om4</literal> are not used and may be set to 0.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>deltap</term>
-                <listitem>
-                    <para>
-                        ripple in the passband. <literal>0&lt;= deltap
-                            &lt;=1
-                        </literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>deltas</term>
-                <listitem>
-                    <para>
-                        ripple in the stopband. <literal>0&lt;= deltas
-                            &lt;=1
-                        </literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>cells</term>
-                <listitem>
-                    <para>realization of the filter as second order cells</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fact</term>
-                <listitem>
-                    <para>normalization constant</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zzeros</term>
-                <listitem>
-                    <para>zeros in the z-domain</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zpoles</term>
-                <listitem>
-                    <para>poles in the z-domain</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Design of iir filter based on <link linkend="syredi">syredi</link>.
-        </para>
-        <para>
-            The filter obtained is <literal>h(z)=fact</literal>*product of the
-            elements of <literal>cells</literal>.
-        </para>
-        <para>That is
-            <literal>hz=fact*prod(cells.num)./prod(cells.den).</literal>
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-[cells,fact,zzeros,zpoles]=eqiir('lp','ellip',[2*%pi/10,4*%pi/10],0.02,0.001)
-h=fact*poly(zzeros,'z')/poly(zpoles,'z')
- ]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="eqfir">eqfir</link>
-            </member>
-            <member>
-                <link linkend="iir">iir</link>
-            </member>
-            <member>
-                <link linkend="syredi">syredi</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/faurre.xml b/scilab/modules/signal_processing/help/fr_FR/filters/faurre.xml
deleted file mode 100644 (file)
index 88393e9..0000000
+++ /dev/null
@@ -1,82 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="faurre">
-    <refnamediv>
-        <refname>faurre</refname>
-        <refpurpose>filter computation by simple Faurre algorithm</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[P,R,T]=faurre(n,H,F,G,R0)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>number of iterations.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>H, F, G</term>
-                <listitem>
-                    <para>
-                        estimated triple from the covariance sequence of <literal>y</literal>.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>R0</term>
-                <listitem>
-                    <para>E(yk*yk')</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>P</term>
-                <listitem>
-                    <para>solution of the Riccati equation after n iterations.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>R, T</term>
-                <listitem>
-                    <para>gain matrix of the filter.</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            This function computes iteratively the minimal solution of the algebraic
-            Riccati equation and gives the matrices <literal>R</literal> and <literal>T</literal> of the
-            filter model.
-            The algorithm tries to compute the solution P as the growing limit of a
-            sequence of matrices Pn such that
-        </para>
-        <programlisting role=""><![CDATA[
-                                     -1
-Pn+1=F*Pn*F'+(G-F*Pn*h')*(R0-H*Pn*H')  *(G'-H*Pn*F')
-       -1
-P0=G*R0 *G'
- ]]></programlisting>
-        <para>
-            Note that this method may not converge,especially when F has poles
-            near the unit circle. Use preferably the srfaur function.
-        </para>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="srfaur">srfaur</link>
-            </member>
-            <member>
-                <link linkend="lindquist">lindquist</link>
-            </member>
-            <member>
-                <link linkend="phc">phc</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/ffilt.xml b/scilab/modules/signal_processing/help/fr_FR/filters/ffilt.xml
deleted file mode 100644 (file)
index 56aa210..0000000
+++ /dev/null
@@ -1,87 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="ffilt">
-    <refnamediv>
-        <refname>ffilt</refname>
-        <refpurpose>coefficients of FIR low-pass</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[x]=ffilt(ft,n,fl,fh)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>ft</term>
-                <listitem>
-                    <para>
-                        filter type where <literal>ft</literal> can take the values
-                    </para>
-                    <variablelist>
-                        <varlistentry>
-                            <term>"lp"  </term>
-                            <listitem>
-                                <para>for low-pass filter</para>
-                            </listitem>
-                        </varlistentry>
-                        <varlistentry>
-                            <term>"hp"  </term>
-                            <listitem>
-                                <para>for high-pass filter</para>
-                            </listitem>
-                        </varlistentry>
-                        <varlistentry>
-                            <term>"bp"  </term>
-                            <listitem>
-                                <para>for band-pass filter</para>
-                            </listitem>
-                        </varlistentry>
-                        <varlistentry>
-                            <term>"sb"  </term>
-                            <listitem>
-                                <para>for stop-band filter</para>
-                            </listitem>
-                        </varlistentry>
-                    </variablelist>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>integer (number of filter samples desired)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fl</term>
-                <listitem>
-                    <para>real (low frequency cut-off)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fh</term>
-                <listitem>
-                    <para>real (high frequency cut-off)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x</term>
-                <listitem>
-                    <para>vector of filter coefficients</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Get <literal>n</literal> coefficients of a FIR low-pass,
-            high-pass, band-pass, or stop-band filter.
-            For low and high-pass filters one cut-off
-            frequency must be specified whose value is
-            given in <literal>fl</literal>. For band-pass and stop-band
-            filters two cut-off frequencies must be
-            specified for which the lower value is in
-            <literal>fl</literal> and the higher value is in <literal>fh</literal>
-        </para>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/filt_sinc.xml b/scilab/modules/signal_processing/help/fr_FR/filters/filt_sinc.xml
deleted file mode 100644 (file)
index 9d701d8..0000000
+++ /dev/null
@@ -1,58 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="filt_sinc">
-    <refnamediv>
-        <refname>filt_sinc</refname>
-        <refpurpose>samples of sinc function</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[x]=filt_sinc(n,fl)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>number of samples</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fl</term>
-                <listitem>
-                    <para>cut-off frequency of the associated low-pass filter in Hertz.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x</term>
-                <listitem>
-                    <para>samples of the sinc function</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Calculate n samples of the function <literal>sin(2*pi*fl*t)/(pi*t)</literal>
-            for <literal>t=-(n-1)/2:(n-1)/2</literal> (i.e. centred around the origin).
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-plot(filt_sinc(100,0.1))
- ]]></programlisting>
-        <scilab:image>
-            plot(filt_sinc(100,0.1))
-        </scilab:image>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="sincd">sincd</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/filter.xml b/scilab/modules/signal_processing/help/fr_FR/filters/filter.xml
deleted file mode 100644 (file)
index 8e50aae..0000000
+++ /dev/null
@@ -1,138 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<!--
-    * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab
-    * Copyright (C) 2004-2007 - INRIA - Vincent COUVERT
-    *
- * Copyright (C) 2012 - 2016 - Scilab Enterprises
- *
- * This file is hereby licensed under the terms of the GNU GPL v2.0,
- * pursuant to article 5.3.4 of the CeCILL v.2.1.
- * This file was originally licensed under the terms of the CeCILL v2.1,
- * and continues to be available under such terms.
- * For more information, see the COPYING file which you should have received
- * along with this program.
-    *
-    -->
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="filter">
-    <refnamediv>
-        <refname>filter</refname>
-        <refpurpose>filters a data sequence using a digital filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[y,zf] = filter(B, A, x [,zi])</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>B</term>
-                <listitem>
-                    <para>real vector : the coefficients of the filter numerator in decreasing power order, or a polynomial.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>A</term>
-                <listitem>
-                    <para>real vector : the coefficients of the filter denominator in decreasing power order, or a polynomial.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x</term>
-                <listitem>
-                    <para>real row vector : the input signal</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zi</term>
-                <listitem>
-                    <para>real row vector of length
-                        <literal>max(length(a),length(b))-1</literal>: the initial
-                        condition relative to a "direct form II transposed" state
-                        space representation. The default value is a vector filled
-                        with zeros.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>y</term>
-                <listitem>
-                    <para>real row vector : the filtered signal. </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zf</term>
-                <listitem>
-                    <para>real row vector : the final state. It can be used to
-                        filter a next batch of the input signal.
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            This function filters a data sequence using a digital
-            filter using a "direct form II transposed"
-            implementation.
-        </para>
-        <para>
-            The filter canonical form is :
-        </para>
-        <para>
-            <latex>
-                \[
-                H(z) = \frac{B(z)}{A(z)} = \frac{b_0 + b_1 z^{-1} + \dots + b_n z^{-n}}{a_0 + a_1 z^{-1} + \dots + a_n z^{-n}}
-                \]
-            </latex>
-        </para>
-        <para>
-            The algorithm uses the highest degree between <literal>degree(a)</literal> and <literal>degree(b)</literal> as value for <literal>n</literal>.
-        </para>
-        <para>
-            If the polynomial form is used for <varname>B</varname> (resp. for <varname>A</varname>) then a polynomial or a scalar must be used for <varname>A</varname> (resp. <varname>B</varname>).
-        </para>
-    </refsection>
-    <refsection>
-        <title>References</title>
-        <para>
-            Oppenheim, A. V. and R.W. Schafer. Discrete-Time Signal Processing, Englewood Cliffs, NJ: Prentice-Hall, 1989, pp. 311-312.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-            x = [1 zeros(1,9)]
-            h = [0 0 1];
-            res = filter(h, 1, x) //This creates a delay of 2 elements
-
-            z = poly(0, "z");
-            B = 1;
-            A = z^2;
-            // B/A is z^(-2)
-            // the resulting filter is also a delay of 2 elements
-            res = filter(B, A, x)
-
-            //Integrator filter
-            x = ones(1,10)
-            B = 1;
-            A = [1 -1];
-            res = filter(B, A, x)
-            ]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="flts">flts</link>
-            </member>
-            <member>
-                <link linkend="rtitr">rtitr</link>
-            </member>
-            <member>
-                <link linkend="ltitr">ltitr</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/find_freq.xml b/scilab/modules/signal_processing/help/fr_FR/filters/find_freq.xml
deleted file mode 100644 (file)
index 8c1e169..0000000
+++ /dev/null
@@ -1,64 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="find_freq">
-    <refnamediv>
-        <refname>find_freq</refname>
-        <refpurpose>parameter compatibility for elliptic filter design</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[m]=find_freq(epsilon,A,n)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>epsilon</term>
-                <listitem>
-                    <para>passband ripple</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>A</term>
-                <listitem>
-                    <para>stopband attenuation</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>filter order</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>m</term>
-                <listitem>
-                    <para>frequency needed for construction of elliptic filter</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Search for m such that <literal>n=K(1-m1)K(m)/(K(m1)K(1-m))</literal>
-            with
-        </para>
-        <para>
-            <literal>m1=(epsilon*epsilon)/(A*A-1)</literal>;
-        </para>
-        <para>
-            If <literal>m = omegar^2/omegac^2</literal>, the parameters
-            <literal>epsilon,A,omegac,omegar</literal> and <literal>n</literal> are then
-            compatible for defining a prototype elliptic filter.
-            Here, <literal>K=%k(m)</literal> is the complete elliptic integral with parameter <literal>m</literal>.
-        </para>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="percentk">%k</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/frmag.xml b/scilab/modules/signal_processing/help/fr_FR/filters/frmag.xml
deleted file mode 100644 (file)
index d52cd11..0000000
+++ /dev/null
@@ -1,117 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="frmag">
-    <refnamediv>
-        <refname>frmag</refname>
-        <refpurpose>magnitude of FIR and IIR filters</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>
-            [xm,fr]=frmag(sys,npts)
-            [xm,fr]=frmag(num,den,npts)
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>sys</term>
-                <listitem>
-                    <para>a single input,
-                        single output discrete transfer function, or a polynomial or
-                        the vector of polynomial coefficients, the filter.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>num</term>
-                <listitem>
-                    <para>a polynomial or the vector of polynomial coefficients,
-                        the numerator of the filter
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>den</term>
-                <listitem>
-                    <para>a polynomial or the vector of polynomial coefficients,
-                        the denominator of the filter (the default value is 1).
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>npts</term>
-                <listitem>
-                    <para>integer, the number of points in frequency response.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>xm</term>
-                <listitem>
-                    <para>vector of magnitude of frequency response at the
-                        points <literal>fr</literal>.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fr</term>
-                <listitem>
-                    <para>points in the normalized frequency domain where magnitude is
-                        evaluated.
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            calculates the magnitude of the frequency responses of
-            FIR and IIR filters. The filter description can be
-            one or two vectors of coefficients, one or two polynomials,
-            or a single output discrete transfer function.
-        </para>
-        <para> the frequency discretization is given by
-            <literal>fr=linspace(0,1/2,npts)</literal>.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-hz=iir(3,'bp','cheb1',[.15 .25],[.08 .03]);
-[hzm,fr]=frmag(hz,256);
-plot(fr,hzm)
-hz=iir(3,'bp','ellip',[.15 .25],[.08 .03]);
-[hzm,fr]=frmag(hz,256);
-plot(fr,hzm,'r')
- ]]></programlisting>
-        <scilab:image><![CDATA[
-hz=iir(3,'bp','cheb1',[.15 .25],[.08 .03]);
-[hzm,fr]=frmag(hz,256);
-plot(fr,hzm)
-hz=iir(3,'bp','ellip',[.15 .25],[.08 .03]);
-[hzm,fr]=frmag(hz,256);
-plot(fr,hzm,'r')
-]]>     </scilab:image>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="iir">iir</link>
-            </member>
-            <member>
-                <link linkend="eqfir">eqfir</link>
-            </member>
-            <member>
-                <link linkend="repfreq">repfreq</link>
-            </member>
-            <member>
-                <link linkend="calfrq">calfrq</link>
-            </member>
-            <member>
-                <link linkend="phasemag">phasemag</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/fsfirlin.xml b/scilab/modules/signal_processing/help/fr_FR/filters/fsfirlin.xml
deleted file mode 100644 (file)
index df39dca..0000000
+++ /dev/null
@@ -1,104 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="fsfirlin">
-    <refnamediv>
-        <refname>fsfirlin</refname>
-        <refpurpose>design of FIR, linear phase filters, frequency sampling technique</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[hst]=fsfirlin(hd,flag)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>hd</term>
-                <listitem>
-                    <para>vector of desired frequency response samples</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>flag</term>
-                <listitem>
-                    <para>is equal to 1 or 2, according to the choice of type 1 or type 2 design</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>hst</term>
-                <listitem>
-                    <para>vector giving the approximated continuous response on a dense grid of frequencies</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            function for the design of FIR, linear phase filters
-            using the frequency sampling technique
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-//
-//Example of how to use the fsfirlin macro for the design
-//of an FIR filter by a frequency sampling technique.
-//
-//Two filters are designed : the first (response hst1) with
-//abrupt transitions from 0 to 1 between passbands and stop
-//bands; the second (response hst2) with one sample in each
-//transition band (amplitude 0.5) for smoothing.
-//
-hd=[zeros(1,15) ones(1,10) zeros(1,39)];//desired samples
-hst1=fsfirlin(hd,1);//filter with no sample in the transition
-hd(15)=.5;hd(26)=.5;//samples in the transition bands
-hst2=fsfirlin(hd,1);//corresponding filter
-pas=1/prod(size(hst1))*.5;
-fg=0:pas:.5;//normalized frequencies grid
-plot2d([1 1].*.fg(1:257)',[hst1' hst2']);
-
-// 2nd example
-hd=[0*ones(1,15) ones(1,10) 0*ones(1,39)];//desired samples
-hst1=fsfirlin(hd,1);//filter with no sample in the transition
-hd(15)=.5;hd(26)=.5;//samples in the transition bands
-hst2=fsfirlin(hd,1);//corresponding filter
-pas=1/prod(size(hst1))*.5;
-fg=0:pas:.5;//normalized frequencies grid
-n=prod(size(hst1))
-plot(fg(1:n),hst1);
-plot2d(fg(1:n)',hst2',[3],"000");
- ]]></programlisting>
-        <scilab:image><![CDATA[
-hd=[zeros(1,15) ones(1,10) zeros(1,39)];//desired samples
-hst1=fsfirlin(hd,1);//filter with no sample in the transition
-hd(15)=.5;hd(26)=.5;//samples in the transition bands
-hst2=fsfirlin(hd,1);//corresponding filter
-pas=1/prod(size(hst1))*.5;
-fg=0:pas:.5;//normalized frequencies grid
-plot2d([1 1].*.fg(1:257)',[hst1' hst2']);
-
-// 2nd example
-hd=[0*ones(1,15) ones(1,10) 0*ones(1,39)];//desired samples
-hst1=fsfirlin(hd,1);//filter with no sample in the transition
-hd(15)=.5;hd(26)=.5;//samples in the transition bands
-hst2=fsfirlin(hd,1);//corresponding filter
-pas=1/prod(size(hst1))*.5;
-fg=0:pas:.5;//normalized frequencies grid
-n=prod(size(hst1))
-plot(fg(1:n),hst1);
-plot2d(fg(1:n)',hst2',[3],"000");
-]]>     </scilab:image>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="ffilt">ffilt</link>
-            </member>
-            <member>
-                <link linkend="wfir">wfir</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/group.xml b/scilab/modules/signal_processing/help/fr_FR/filters/group.xml
deleted file mode 100644 (file)
index 4861d6f..0000000
+++ /dev/null
@@ -1,100 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="group">
-    <refnamediv>
-        <refname>group</refname>
-        <refpurpose>group delay for digital filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>
-            [tg [,fr]] = group(npts, H) (call with a siso transfert function)
-            [tg [,fr]] = group(npts, C) (call with a vector of transfert functions, cascaded second order representation)
-
-            [tg [,fr]] = group(npts, F) (call with the vector of an FIR filter coefficients)
-            [tg [,fr]] = group(npts, a1i, a2i, b1i, b2i) (call with 4 vectors of numbers, cascaded second order Deczky representation)
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>npts</term>
-                <listitem>
-                    <para>integer : number of points desired in calculation of group delay</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>a1i</term>
-                <listitem>
-                    <para>in coefficient, polynomial, rational polynomial, or cascade polynomial form this variable is the transfer function of the filter. In coefficient polynomial form this is a vector of coefficients (see below).</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>a2i</term>
-                <listitem>
-                    <para>in coeff poly form this is a vector of coeffs</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>b1i</term>
-                <listitem>
-                    <para>in coeff poly form this is a vector of coeffs</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>b2i</term>
-                <listitem>
-                    <para>in coeff poly form this is a vector of coeffs</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>tg</term>
-                <listitem>
-                    <para>values of group delay evaluated on the grid fr</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fr</term>
-                <listitem>
-                    <para>grid of normalized frequency values where group delay is evaluated</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Calculate the group delay of a digital filter
-            with transfer function h(z).
-        </para>
-        <para>
-            The filter specification can be in coefficient form,
-            polynomial form, rational polynomial form, cascade
-            polynomial form, or in coefficient polynomial form.
-        </para>
-        <para>
-            In the coefficient polynomial form the transfer function is
-            formulated by the following expression
-        </para>
-        <para>
-            <literal>h(z)=prod(a1i+a2i*z+z**2)/prod(b1i+b2i*z+z^2)</literal>
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-        s = poly(0, "s");
-        h_cont = syslin("c", 1/(s-10));
-        h = ss2tf(cls2dls(tf2ss(h_cont), 0.1));
-        [tg, fr] = group(100, h);
-        plot(fr, tg)
- ]]></programlisting>
-        <scilab:image><![CDATA[
-s = poly(0, "s");
-h_cont = syslin("c", 1/(s-10));
-h = ss2tf(cls2dls(tf2ss(h_cont), 0.1));
-[tg, fr] = group(100, h);
-plot(fr, tg)
-]]>     </scilab:image>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/hilbert.xml b/scilab/modules/signal_processing/help/fr_FR/filters/hilbert.xml
deleted file mode 100644 (file)
index cc98b66..0000000
+++ /dev/null
@@ -1,83 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="hilbert">
-    <refnamediv>
-        <refname>hilbert</refname>
-        <refpurpose>Discrete-time analytic signal computation of a real signal  using Hilbert transform </refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>x=hilbert(xr)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>xr</term>
-                <listitem>
-                    <para>real vector : the real signal samples</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x</term>
-                <listitem>
-                    <para>Complex vector: the discrete-time analytic signal.</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>Returns theanalytic signal, from a real data sequence.</para>
-        <para>
-            The analytic signal <literal>x= xr + i*xi</literal> has a real part, <literal>xr</literal>, which
-            is the original data, and an imaginary part, <literal>xi</literal>, which contains
-            the Hilbert transform. The imaginary part is a version of the
-            original real sequence with a 90° phase shift.
-        </para>
-    </refsection>
-    <refsection>
-        <title>References</title>
-        <para>
-            <literal>
-                <ulink url="http://ieeexplore.ieee.org/iel5/78/16975/00782222.pdf?arnumber=782222">http://ieeexplore.ieee.org/iel5/78/16975/00782222.pdf?arnumber=782222</ulink>
-            </literal>
-        </para>
-        <para>
-            Marple, S.L., "Computing the discrete-time analytic signal via FFT,"
-            IEEE Transactions on Signal Processing, Vol. 47, No.9 (September
-            1999), pp.2600-2603
-        </para>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="window">window</link>
-            </member>
-            <member>
-                <link linkend="hilb">hil</link>
-            </member>
-        </simplelist>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-//compare the discrete-time analytic signal imaginary part of the impulse real signal
-// with the FIR approximation of the Hilbert transform filter
-m=25;
-n=2*m+1;
-y=hilbert(eye(n,1));
-h=hilb(n)';
-h=[h((m+1):$);h(1:m)];
-plot([imag(y) h])
- ]]></programlisting>
-        <scilab:image>
-            m=25;
-            n=2*m+1;
-            y=hilbert(eye(n,1));
-            h=hilb(n)';
-            h=[h((m+1):$);h(1:m)];
-            plot([imag(y) h])
-        </scilab:image>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/iirgroup.xml b/scilab/modules/signal_processing/help/fr_FR/filters/iirgroup.xml
deleted file mode 100644 (file)
index 8e88c60..0000000
+++ /dev/null
@@ -1,66 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="iirgroup">
-    <refnamediv>
-        <refname>iirgroup</refname>
-        <refpurpose>group delay Lp IIR filter optimization</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[lt,grad]=iirgroup(p,r,theta,omega,wt,td)
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>p</term>
-                <listitem>
-                    <para>Lp criterion</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>r</term>
-                <listitem>
-                    <para>vector of the module of the poles and the zeros of the filters</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>theta</term>
-                <listitem>
-                    <para>vector of the argument of the poles and the zeros of the filters</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>omega</term>
-                <listitem>
-                    <para>frequencies where the filter specifications are given</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>wt</term>
-                <listitem>
-                    <para>weighting function for and the group delay</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>td</term>
-                <listitem>
-                    <para>desired group delay</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>lt, grad</term>
-                <listitem>
-                    <para>criterium and gradient values</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            optimization of IIR filters for the Lp criterium for the
-            the group delay. (Rabiner &amp; Gold pp270-273).
-        </para>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/iirlp.xml b/scilab/modules/signal_processing/help/fr_FR/filters/iirlp.xml
deleted file mode 100644 (file)
index 7c435d9..0000000
+++ /dev/null
@@ -1,75 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="iirlp">
-    <refnamediv>
-        <refname>iirlp</refname>
-        <refpurpose>Lp IIR filter optimization</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[cost,grad,ind]=iirlp(x,ind,p,[flag],lambda,omega,ad,wa,td,wt)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>p</term>
-                <listitem>
-                    <para>Lp criterion</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x</term>
-                <listitem>
-                    <para>1X2 vector of the module and argument of the poles and the zeros of the filters</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>flag</term>
-                <listitem>
-                    <para>
-                        string : <literal>'a'</literal> for amplitude, 'gd' for group delay; default case for amplitude and group delay.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>omega</term>
-                <listitem>
-                    <para>frequencies where the filter specifications are given</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>wa,wt</term>
-                <listitem>
-                    <para>weighting functions for the amplitude and the group delay</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>lambda</term>
-                <listitem>
-                    <para>
-                        weighting (with <literal>1-lambda</literal>) of the costs (<literal>'a'</literal> and <literal>'gd'</literal> for getting the global cost.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>ad, td</term>
-                <listitem>
-                    <para>desired amplitude and group delay</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>cost, grad</term>
-                <listitem>
-                    <para>criterium and gradient values</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            optimization of IIR filters for the Lp criterium for the
-            amplitude and/or the group delay. (Rabiner &amp; Gold pp270-273).
-        </para>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/kalm.xml b/scilab/modules/signal_processing/help/fr_FR/filters/kalm.xml
deleted file mode 100644 (file)
index 95c6ba5..0000000
+++ /dev/null
@@ -1,189 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="kalm">
-    <refnamediv>
-        <refname>kalm</refname>
-        <refpurpose>Kalman update</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[x1,p1,x,p]=kalm(y,x0,p0,f,g,h,q,r)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>f,g,h</term>
-                <listitem>
-                    <para>current system matrices</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>q, r</term>
-                <listitem>
-                    <para>covariance matrices of dynamics and observation noise</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x0,p0</term>
-                <listitem>
-                    <para>state estimate and error variance at t=0 based on data up to t=-1</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>y</term>
-                <listitem>
-                    <para>current observation Output</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x1,p1</term>
-                <listitem>
-                    <para>updated estimate and error covariance at t=1 based on data up to t=0</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x,p</term>
-                <listitem>
-                    <para>updated estimate and error covariance at t=0  based on data up to t=0</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            This function gives the Kalman update and error covariance. To do this, we have to enter <varname>f</varname>,
-            <varname>g</varname>, <varname>h</varname> which are based on the state space model:
-        </para>
-        <para>
-            <literal>
-                x(k+1)=<varname>f</varname>*x(k)+<varname>g</varname>*u(k)+v(k)
-            </literal>
-        </para>
-        <para>
-            <literal>
-                y(k)=<varname>h</varname>*x(k)+w(k)
-            </literal>
-        </para>
-        <para>
-            with <literal>v(k)</literal> (resp. <literal>w(k)</literal>) is the process noise (resp. the observation noise)
-            supposed to be drawn from a zero mean Gaussian white noise with the covariance <varname>q</varname> (resp. <varname>r</varname>).
-        </para>
-        <para>
-            Precisely, Kalman filter is a recursive estimator which gives the estimate of the current state and the error covariance.
-            Its advantage is the fact that it only needs the estimated state from the previous step and the current measurement.
-        </para>
-        <para>
-            Algorithm:
-        </para>
-        <itemizedlist>
-            <listitem>
-                <para>
-                    Innovation (output error):
-                    <literal>
-                        E=<varname>y</varname>-<varname>h</varname>*<varname>x0</varname>
-                    </literal>
-                </para>
-            </listitem>
-
-            <listitem>
-                <para>
-                    Output Error covariance:
-                    <literal>
-                        S=<varname>h</varname>*<varname>p0</varname>*<varname>h</varname>'+<varname>r</varname>
-                    </literal>
-                </para>
-            </listitem>
-            <listitem>
-                <para>
-                    Kalman gain:
-                    <literal>
-                        K=<varname>p0</varname>*<varname>h</varname>'*S^-1
-                    </literal>
-                </para>
-            </listitem>
-            <listitem>
-                <para>
-                    Correction of state estimation:
-                    <literal>
-                        <varname>x</varname>=<varname>x0</varname>+K*E
-                    </literal>
-                </para>
-            </listitem>
-            <listitem>
-                <para>
-                    Correction of estimation of error covariance:
-                    <literal>
-                        <varname>p</varname>=<varname>p0</varname>-K*<varname>h</varname>*<varname>p0</varname>
-                    </literal>
-                </para>
-            </listitem>
-            <listitem>
-                <para>
-                    State prediction:
-                    <literal>
-                        <varname>x1</varname>=<varname>f</varname>*<varname>x</varname>
-                    </literal>
-                </para>
-            </listitem>
-            <listitem>
-                <para>
-                    Error covariance prediction:
-                    <literal>
-                        <varname>p1</varname>=<varname>f</varname>*<varname>p</varname>*<varname>f</varname>'+<varname>g</varname>*<varname>q</varname>*<varname>g</varname>'
-                    </literal>
-                </para>
-            </listitem>
-        </itemizedlist>
-    </refsection>
-    <refsection>
-        <title>Example: Extraction of a sinusoid from noise with Kalman filter</title>
-        <programlisting role="Example"><![CDATA[
-// Construction of the sinusoid
-w=%pi/4; // angular frequency
-T=0.1; // period
-t=0:T:500;
-signal=cos(w*t);
-// Sinusoid with noise
-v=rand(t,"normal");
-y=signal+v;
-// Plot the sinusoid with noise
-subplot(2,1,1);
-plot(t,y);
-xtitle("sinusoid with noise","t");
-// System
-n=2; // system order
-f=[cos(w*T) -sin(w*T); sin(w*T) cos(w*T)];
-g=0;
-h=[1 0];
-p0=[1000 0; 0 0];
-R=1;
-Q=0;
-x0=zeros(n,1);
-// Initialize for loop
-x1=x0;
-p1=p0;
-// Kalman filter
-for i=1:length(t)-1
-    [x1(:,i+1),p1,x,p]=kalm(y(i),x1(:,i),p1,f,g,h,Q,R);
-end
-// Plot the results (in red) to compare with the sinusoid (in green)
-subplot(2,1,2);
-plot(t,signal,"color","green");
-plot(t,x1(1,:),"color","red");
-xtitle("Comparison between sinusoid (green) and extraction with Kalman filter (red)","t");
-]]>
-        </programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="srkf">srkf</link>
-            </member>
-            <member>
-                <link linkend="sskf">sskf</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/lev.xml b/scilab/modules/signal_processing/help/fr_FR/filters/lev.xml
deleted file mode 100644 (file)
index e6022fe..0000000
+++ /dev/null
@@ -1,73 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="lev">
-    <refnamediv>
-        <refname>lev</refname>
-        <refpurpose>Yule-Walker equations (Levinson's algorithm)  </refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[ar, sigma2, rc]=lev(r)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>r</term>
-                <listitem>
-                    <para>correlation coefficients</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>ar</term>
-                <listitem>
-                    <para>auto-Regressive model parameters</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>sigma2</term>
-                <listitem>
-                    <para>scale constant</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>rc</term>
-                <listitem>
-                    <para>reflection coefficients</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            This function resolves the Yule-Walker equations using Levinson's algorithm. Generally, it is used to estimate the coefficients of an autoregressive process.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Example</title>
-        <programlisting role="Example"><![CDATA[
-b=1; //numerator
-a=[1 -0.7 0.8]; //denominator
-x=[1 zeros(1,99)]; //input=impulse
-data=filter(b,a,x); //real data
-a2=lev(data); //modelized data
-a2=a2/a2(1); //normalization
-m_data=filter(1,a2,x);
-// Compare real data and modelized data
-plot(data,"color","blue","lineStyle","none","marker","d");
-plot(m_data,"color","red","lineStyle","none","marker","d");
-]]>
-        </programlisting>
-        <scilab:image>
-            b=1;
-            a=[1 -0.7 0.8];
-            x=[1 zeros(1,99)];
-            data=filter(b,a,x);
-            a2=lev(data);
-            a2=a2/a2(1);
-            m_data=filter(1,a2,x);
-            plot(data,"color","blue","lineStyle","none","marker","d");
-            plot(m_data,"color","red","lineStyle","none","marker","d");
-        </scilab:image>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/levin.xml b/scilab/modules/signal_processing/help/fr_FR/filters/levin.xml
deleted file mode 100644 (file)
index ea59c48..0000000
+++ /dev/null
@@ -1,184 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns3="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:id="levin" xml:lang="fr">
-    <refnamediv>
-        <refname>levin</refname>
-        <refpurpose>Toeplitz system solver by Levinson algorithm
-            (multidimensional)
-        </refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[la,sig]=levin(n,cov)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>A scalar with integer value: the maximum order of the
-                        filter
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>cov</term>
-                <listitem>
-                    <para>
-                        A <literal>(nlag*d) x d</literal> matrix. It contains the
-                        <literal>Rk</literal> (<literal>d x d</literal> matrices for a
-                        <literal>d</literal>-dimensional process) stored in the following
-                        way :
-                    </para>
-                    <para>
-                        <latex>
-                            \begin{eqnarray}
-                            \begin{pmatrix}
-                            R_0\\R_1\\R_2\\ \vdots \\R_{nlags}
-                            \end{pmatrix}
-                            \end{eqnarray}
-                        </latex>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>la</term>
-                <listitem>
-                    <para>A list, the successively calculated Levinson polynomials
-                        (degree 1 to <literal>n</literal>), with coefficients
-                        <literal>Ak</literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>sig</term>
-                <listitem>
-                    <para>A list, the successive mean-square errors.</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>function which solves recursively on n the following Toeplitz system
-            (normal equations)
-        </para>
-        <para>
-            <latex>
-                \begin{eqnarray}
-                \begin{pmatrix}
-                I&amp;-A_1&amp;\cdots&amp;-A_n
-                \end{pmatrix}
-                \ast
-                \begin{pmatrix}
-                R_1&amp;R_2&amp;\cdots&amp;R_n \\
-                R_0&amp;R_1&amp;\cdots&amp;R_{n-1} \\
-                R_{-1}&amp;R_0&amp;\cdots&amp;R_{n-2} \\
-                \vdots&amp;\vdots&amp;\cdots&amp;\vdots \\
-                R_{2-n}&amp;R_{3-n}&amp;\cdots&amp;R_1 \\
-                R_{1-n}&amp;R_{2-n}&amp;\cdots&amp;R_0
-                \end{pmatrix}
-                = 0
-                \end{eqnarray}
-            </latex>
-        </para>
-        <para>
-            where {<literal>Rk;k=1:nlag</literal>} is the sequence of
-            <literal>nlag</literal> empirical covariances
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-//We use the 'levin' macro for solving the normal equations
-//on two examples: a one-dimensional and a two-dimensional process.
-//We need the covariance sequence of the stochastic process.
-//This example may usefully be compared with the results from
-//the 'phc' macro (see the corresponding help and example in it)
-//
-//
-//1) A one-dimensional process
-//   -------------------------
-//
-//We generate the process defined by two sinusoids (1Hz and 2 Hz)
-//in additive Gaussian noise (this is the observed process);
-//the simulated process is sampled at 10 Hz (step 0.1 in t, underafter).
-
-t1=0:.1:100;rand('normal');
-y1=sin(2*%pi*t1)+sin(2*%pi*2*t1);y1=y1+rand(y1);plot(t1,y1);
-
-//covariance of y1
-
-nlag=128;
-c1=corr(y1,nlag);
-c1=c1';//c1 needs to be given columnwise (see the section PARAMETERS of this help)
-
-//compute the filter for a maximum order of n=10
-//la is a list-type variable each element of which
-//containing the filters of order ranging from 1 to n; (try varying n)
-//in the d-dimensional case this is a matrix polynomial (square, d X d)
-//sig gives, the same way, the mean-square error
-
-n=15;
-[la1,sig1]=levin(n,c1);
-
-//verify that the roots of 'la' contain the
-//frequency spectrum of the observed process y
-//(remember that y is sampled -in our example
-//at 10Hz (T=0.1s) so that we need to retrieve
-//the original frequencies (1Hz and 2 Hz) through
-//the log and correct scaling by the frequency sampling)
-//we verify this for each filter order
-
-for i=1:n, s1=roots(la1(i));s1=log(s1)/2/%pi/.1;
-
-//now we get the estimated poles (sorted, positive ones only !)
-
-s1=gsort(imag(s1));s1=s1(1:i/2);end;
-
-//the last two frequencies are the ones really present in the observed
-//process ---> the others are "artifacts" coming from the used model size.
-//This is related to the rather difficult problem of order estimation.
-//
-//2) A 2-dimensional process
-//   -----------------------
-//(4 frequencies 1, 2, 3, and 4 Hz, sampled at 0.1 Hz :
-//   |y_1|        y_1=sin(2*Pi*t)+sin(2*Pi*2*t)+Gaussian noise
-// y=|   | with :
-//   |y_2|        y_2=sin(2*Pi*3*t)+sin(2*Pi*4*t)+Gaussian noise
-
-d=2;dt=0.1;
-nlag=64;
-t2=0:2*%pi*dt:100;
-y2=[sin(t2)+sin(2*t2)+rand(t2);sin(3*t2)+sin(4*t2)+rand(t2)];
-c2=[];
-for j=1:2, for k=1:2, c2=[c2;corr(y2(k,:),y2(j,:),nlag)];end;end;
-c2=matrix(c2,2,128);cov=[];
-for j=1:64,cov=[cov;c2(:,(j-1)*d+1:j*d)];end;//covar. columnwise
-c2=cov;
-
-//in the multidimensional case, we have to compute the
-//roots of the determinant of the matrix polynomial
-//(easy in the 2-dimensional case but tricky if d>=3 !).
-//We just do that here for the maximum desired
-//filter order (n); mp is the matrix polynomial of degree n
-
-[la2,sig2]=levin(n,c2);
-mp=la2(n);determinant=mp(1,1)*mp(2,2)-mp(1,2)*mp(2,1);
-s2=roots(determinant);s2=log(s2)/2/%pi/0.1;//same trick as above for 1D process
-s2=gsort(imag(s2));s2=s2(1:d*n/2);//just the positive ones !
-
-//There the order estimation problem is seen to be much more difficult !
-//many artifacts ! The 4 frequencies are in the estimated spectrum
-//but beneath many non relevant others.
- ]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="phc">phc</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/lindquist.xml b/scilab/modules/signal_processing/help/fr_FR/filters/lindquist.xml
deleted file mode 100644 (file)
index 54b96ce..0000000
+++ /dev/null
@@ -1,95 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="lindquist">
-    <refnamediv>
-        <refname>lindquist</refname>
-        <refpurpose>Lindquist's algorithm</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[P,R,T]=lindquist(n,H,F,G,R0)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>number of iterations.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>H, F, G</term>
-                <listitem>
-                    <para>
-                        estimated triple from the covariance sequence of <literal>y</literal>.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>R0</term>
-                <listitem>
-                    <para>E(yk*yk')</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>P</term>
-                <listitem>
-                    <para>solution of the Riccati equation after n iterations.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>R, T</term>
-                <listitem>
-                    <para>gain matrices of the filter.</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            computes iteratively the minimal solution of the algebraic
-            Riccati equation and gives the matrices <literal>R</literal> and <literal>T</literal> of the
-            filter model, by the Lindquist's algorithm.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Example</title>
-        <programlisting role="example"><![CDATA[
-//Generate signal
-x=%pi/10:%pi/10:102.4*%pi;
-y=[1; 1] * sin(x) + [sin(2*x); sin(1.9*x)] + rand(2,1024,"normal");
-
-//Compute correlations
-c=[];
-for j=1:2
-   for k=1:2
-     c=[c;corr(y(k,:),y(j,:),64)];
-   end
-end
-c=matrix(c,2,128);
-
-//Find H,F,G with 6 states
-hk=hank(20,20,c);
-[H,F,G]=phc(hk,2,6);
-
-//Solve Riccati equation
-R0=c(1:2,1:2);
-[P,R,T]=lindquist(100,H,F,G,R0);
-]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="srfaur">srfaur</link>
-            </member>
-            <member>
-                <link linkend="faurre">faurre</link>
-            </member>
-            <member>
-                <link linkend="phc">phc</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/remez.xml b/scilab/modules/signal_processing/help/fr_FR/filters/remez.xml
deleted file mode 100644 (file)
index 94195b8..0000000
+++ /dev/null
@@ -1,144 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns3="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:id="remez" xml:lang="fr">
-    <refnamediv>
-        <refname>remez</refname>
-        <refpurpose>Remez exchange algorithm for the weighted chebyshev
-            approximation of a continuous function with a sum of cosines.
-        </refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>an=remez(guess,mag,fgrid,weight)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>guess</term>
-                <listitem>
-                    <para>
-                        real array of size <literal>n+2 the </literal>initial
-                        guess
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fgrid</term>
-                <listitem>
-                    <para>
-                        real array of size <literal>ng</literal>: the grid of
-                        normalized frequency points in [0,.5[
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>mag</term>
-                <listitem>
-                    <para>
-                        real array of size <literal>ng</literal>: the desired
-                        magnitude on grid <literal>fg</literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>weight</term>
-                <listitem>
-                    <para>
-                        real array of size <literal>ng</literal>: weighting function
-                        on error on grid <literal>fg</literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>an</term>
-                <listitem>
-                    <para>
-                        real array of size <literal>n</literal>: cosine
-                        coefficients
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>Minimax approximation of a frequency domain magnitude response. The
-            approximation takes the form
-        </para>
-        <programlisting role=""><![CDATA[
-h = sum[a(i)*cos(weight)], i=1:n
- ]]></programlisting>
-        <para>An FIR, linear-phase filter can be obtained from the output of
-            <literal>remez</literal> by using the following commands:
-        </para>
-        <programlisting role=""><![CDATA[
-hn(1:nc-1)=an(nc:-1:2)/2;
-hn(nc)=an(1);
-hn(nc+1:2*nc-1)=an(2:nc)/2;
- ]]></programlisting>
-        <para>
-            This function is mainly intended to be called by the <link linkend="remezb">remezb function</link>.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Bibliography</title>
-        <para>E.W. Cheney, Introduction to Approximation Theory, McGraw-Hill,
-            1966
-        </para>
-        <para>
-            <ulink url="http://en.wikipedia.org/wiki/Remez_algorithm">http://en.wikipedia.org/wiki/Remez_algorithm</ulink>
-        </para>
-    </refsection>
-    <refsection>
-        <title>References</title>
-        <para>
-            This function is based on the fortran code <literal>remez.f
-            </literal>
-            written by:
-        </para>
-        <itemizedlist>
-            <listitem>
-                <para>James H. Mcclellan, department of electrical engineering and
-                    computer science, Massachusetts Institute of Technology, Cambridge,
-                    Massachussets. 02139
-                </para>
-            </listitem>
-            <listitem>
-                <para>Thomas W. Parks, department of electrical engineering, Rice
-                    university, Houston, Texas 77001
-                </para>
-            </listitem>
-            <listitem>
-                <para>Thomas W. Parks, department of electrical engineering, Rice
-                    university, Houston, Texas 77001
-                </para>
-            </listitem>
-        </itemizedlist>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-nc=21;
-ngrid=nc*250;
-fgrid=.5*(0:(ngrid-1))/(ngrid-1);
-mag(1:ngrid/2)=ones(1:ngrid/2);
-mag(ngrid/2+1:ngrid)=0*ones(1:ngrid/2);
-weight=ones(fgrid);
-guess=round(1:ngrid/nc:ngrid);
-guess(nc+1)=ngrid;
-guess(nc+2)=ngrid;
-an=remez(guess,mag,fgrid,weight);
- ]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="remezb">remezb</link>
-            </member>
-            <member>
-                <link linkend="eqfir">eqfir</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/remezb.xml b/scilab/modules/signal_processing/help/fr_FR/filters/remezb.xml
deleted file mode 100644 (file)
index 58cc994..0000000
+++ /dev/null
@@ -1,159 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="remezb">
-    <refnamediv>
-        <refname>remezb</refname>
-        <refpurpose>Minimax approximation of magnitude response</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[an]=remezb(nc,fg,ds,wt)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>nc</term>
-                <listitem>
-                    <para>Number of cosine functions</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fg</term>
-                <listitem>
-                    <para>Grid of frequency points in [0,.5)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>ds</term>
-                <listitem>
-                    <para>
-                        Desired magnitude on grid <literal>fg</literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>wt</term>
-                <listitem>
-                    <para>
-                        Weighting function on error on grid <literal>fg</literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>an</term>
-                <listitem>
-                    <para>Cosine filter coefficients</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Minimax approximation of a frequency domain
-            magnitude response. The approximation takes
-            the form <literal>h = sum[a(n)*cos(wn)]</literal>
-            for n=0,1,...,nc. An FIR, linear-phase filter
-            can be obtained from the output of the function
-            by using the following commands
-        </para>
-        <programlisting role="no-scilab-exec"><![CDATA[
-hn(1:nc-1)=an(nc:-1:2)/2;
-hn(nc)=an(1);
-hn(nc+1:2*nc-1)=an(2:nc)/2;
- ]]></programlisting>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-// Choose the number of cosine functions and create a dense grid
-// in [0,.24) and [.26,.5)
-nc=21;ngrid=nc*16;
-fg=.24*(0:ngrid/2-1)/(ngrid/2-1);
-fg(ngrid/2+1:ngrid)=fg(1:ngrid/2)+.26*ones(1:ngrid/2);
-
-// Specify a low pass filter magnitude for the desired response
-ds(1:ngrid/2)=ones(1:ngrid/2);
-ds(ngrid/2+1:ngrid)=zeros(1:ngrid/2);
-
-// Specify a uniform weighting function
-wt=ones(fg);
-
-// Run remezb
-an=remezb(nc,fg,ds,wt)
-
-// Make a linear phase FIR filter
-hn(1:nc-1)=an(nc:-1:2)/2;
-hn(nc)=an(1);
-hn(nc+1:2*nc-1)=an(2:nc)/2;
-
-// Plot the filter's magnitude response
-plot(.5*(0:255)/256,frmag(hn,256));
-
-// Choose the number of cosine functions and create a dense grid in [0,.5)
-nc=21; ngrid=nc*16;
-fg=.5*(0:(ngrid-1))/ngrid;
-
-// Specify a triangular shaped magnitude for the desired response
-ds(1:ngrid/2)=(0:ngrid/2-1)/(ngrid/2-1);
-ds(ngrid/2+1:ngrid)=ds(ngrid/2:-1:1);
-
-// Specify a uniform weighting function
-wt=ones(fg);
-
-// Run remezb
-an=remezb(nc,fg,ds,wt)
-
-// Make a linear phase FIR filter
-hn(1:nc-1)=an(nc:-1:2)/2;
-hn(nc)=an(1);
-hn(nc+1:2*nc-1)=an(2:nc)/2;
-
-// Plot the filter's magnitude response
-plot(.5*(0:255)/256,frmag(hn,256));
- ]]></programlisting>
-
-        <scilab:image>
-            nc=21;ngrid=nc*16;
-            fg=.24*(0:ngrid/2-1)/(ngrid/2-1);
-            fg(ngrid/2+1:ngrid)=fg(1:ngrid/2)+.26*ones(1:ngrid/2);
-
-            ds(1:ngrid/2)=ones(1:ngrid/2);
-            ds(ngrid/2+1:ngrid)=zeros(1:ngrid/2);
-
-            wt=ones(fg);
-
-            an=remezb(nc,fg,ds,wt)
-
-            hn(1:nc-1)=an(nc:-1:2)/2;
-            hn(nc)=an(1);
-            hn(nc+1:2*nc-1)=an(2:nc)/2;
-
-            plot(.5*(0:255)/256,frmag(hn,256));
-
-            nc=21; ngrid=nc*16;
-            fg=.5*(0:(ngrid-1))/ngrid;
-
-            ds(1:ngrid/2)=(0:ngrid/2-1)/(ngrid/2-1);
-            ds(ngrid/2+1:ngrid)=ds(ngrid/2:-1:1);
-
-            wt=ones(fg);
-
-            an=remezb(nc,fg,ds,wt)
-
-            hn(1:nc-1)=an(nc:-1:2)/2;
-            hn(nc)=an(1);
-            hn(nc+1:2*nc-1)=an(2:nc)/2;
-
-            plot(.5*(0:255)/256,frmag(hn,256));
-        </scilab:image>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="eqfir">eqfir</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/srfaur.xml b/scilab/modules/signal_processing/help/fr_FR/filters/srfaur.xml
deleted file mode 100644 (file)
index e1aa32d..0000000
+++ /dev/null
@@ -1,106 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="srfaur">
-    <refnamediv>
-        <refname>srfaur</refname>
-        <refpurpose>square-root algorithm</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[p,s,t,l,rt,tt]=srfaur(h,f,g,r0,n,p,s,t,l)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>h, f, g</term>
-                <listitem>
-                    <para>convenient matrices of the state-space model.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>r0</term>
-                <listitem>
-                    <para>E(yk*yk').</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>number of iterations.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>p</term>
-                <listitem>
-                    <para>estimate of the solution after n iterations.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>s, t, l</term>
-                <listitem>
-                    <para>intermediate matrices for  successive iterations;</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>rt, tt</term>
-                <listitem>
-                    <para>
-                        gain matrices of the filter model after <literal>n</literal> iterations.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>p, s, t, l</term>
-                <listitem>
-                    <para>
-                        may be given as input if more than one recursion is desired (evaluation of intermediate values of <literal>p</literal>).
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            square-root algorithm for the algebraic Riccati equation.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-//GENERATE SIGNAL
-x=%pi/10:%pi/10:102.4*%pi;
-rand('seed',0);rand('normal');
-y=[1;1]*sin(x)+[sin(2*x);sin(1.9*x)]+rand(2,1024);
-
-//COMPUTE CORRELATIONS
-c=[];for j=1:2,for k=1:2,c=[c;corr(y(k,:),y(j,:),64)];end;end
-c=matrix(c,2,128);
-
-//FINDING H,F,G with 6 states
-hk=hank(20,20,c);
-[H,F,G]=phc(hk,2,6);
-
-//SOLVING RICCATI EQN
-r0=c(1:2,1:2);
-[P,s,t,l,Rt,Tt]=srfaur(H,F,G,r0,200);
-
-//Make covariance matrix exactly symmetric
-Rt=(Rt+Rt')/2
- ]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="phc">phc</link>
-            </member>
-            <member>
-                <link linkend="faurre">faurre</link>
-            </member>
-            <member>
-                <link linkend="lindquist">lindquist</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/srkf.xml b/scilab/modules/signal_processing/help/fr_FR/filters/srkf.xml
deleted file mode 100644 (file)
index f7ed71e..0000000
+++ /dev/null
@@ -1,82 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="srkf">
-    <refnamediv>
-        <refname>srkf</refname>
-        <refpurpose>square root Kalman filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[x1,p1]=srkf(y,x0,p0,f,h,q,r)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>f, h</term>
-                <listitem>
-                    <para>current system matrices</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>q, r</term>
-                <listitem>
-                    <para>covariance matrices of dynamics and observation noise</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x0, p0</term>
-                <listitem>
-                    <para>state estimate and error variance at t=0 based on data up to t=-1</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>y</term>
-                <listitem>
-                    <para>current observation Output</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x1, p1</term>
-                <listitem>
-                    <para>updated estimate and error covariance at t=1 based on data up to t=0</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            This function is the square root form of Kalman filter. It is more efficient than the simple Kalman filter in term of numerical stability,
-            especially if dynamic noise covariance <varname>q</varname> is small. In effect, that can provock an indefinite numerical representation
-            of the state covariance matrix <literal>p</literal>, whereas <literal>p</literal> is positive definite. So, the goal of <function>srkf</function>
-            is to propagate <literal>p</literal> using a Cholesky factorization algorithm. These factors can be updated at each step of the algorithm, which
-            allows to keep <literal>p</literal> in its basic form.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Example</title>
-        <programlisting role="example"><![CDATA[
-f=[0 0 1; 0 1 0; 2 3 4]; //State matrix
-g=[1;-1;1]; //Input matrix
-h=[1 1 0; 0 1 0; 0 0 0]; //Output matrix
-Q=[3 2 1; 2 2 1; 1 1 1]; //Covariance matrix of dynamic noise
-R=[2 1 1; 1 1 1; 1 1 2]; //Covariance matrix of observation noise
-// Initialisation
-p0=[6 3 2; 3 5 2; 2 2 4];
-x0=[1;1;1];
-y=[2 8 7]'; // Current observation output matrix
-[x1,p1]=srkf(y,x0,p0,f,h,Q,R)
-]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="kalm">kalm</link>
-            </member>
-            <member>
-                <link linkend="sskf">sskf</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/sskf.xml b/scilab/modules/signal_processing/help/fr_FR/filters/sskf.xml
deleted file mode 100644 (file)
index 41c5045..0000000
+++ /dev/null
@@ -1,95 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="sskf">
-    <refnamediv>
-        <refname>sskf</refname>
-        <refpurpose>steady-state Kalman filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>
-            xe = sskf(y,f,h,q,r,x0)
-            [xe, pe]=sskf(y,f,h,q,r,x0)
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>y</term>
-                <listitem>
-                    <para>
-                        data in form <literal>[y0,y1,...,yn]</literal>, <literal>yk</literal> a column vector
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>f</term>
-                <listitem>
-                    <para>system matrix dim(NxN)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>h</term>
-                <listitem>
-                    <para>observations matrix dim(MxN)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>q</term>
-                <listitem>
-                    <para>dynamics noise matrix dim(NxN)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>r</term>
-                <listitem>
-                    <para>observations noise matrix dim(MxM)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x0</term>
-                <listitem>
-                    <para>initial state estimate</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>xe</term>
-                <listitem>
-                    <para>estimated state</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>pe</term>
-                <listitem>
-                    <para>steady-state error covariance</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            steady-state Kalman filter
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-rand("seed",5);
-rand("normal");
-q=[.03 0.01;.01 0.03];
-u=rand(2,11);
-f=[1.1 0.1;0 0.8];
-g=(chol(q))';
-m0=[10 10]';
-p0=[2 0;0 2];
-x0=m0+(chol(p0))'*rand(2,1);
-x=ltitr(f,g,u,x0);
-r=[2 0;0 2];
-v=(chol(r))'*rand(2,11);
-y=x+v;
-h=eye(2,2);
-[xe pe]=sskf(y,f,h,q,r,m0)
- ]]></programlisting>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/syredi.xml b/scilab/modules/signal_processing/help/fr_FR/filters/syredi.xml
deleted file mode 100644 (file)
index 3adbb7f..0000000
+++ /dev/null
@@ -1,167 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns4="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:id="syredi" xml:lang="fr">
-    <refnamediv>
-        <refname>syredi</refname>
-        <refpurpose>Design of iir filters, syredi code interface</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[fact,b2,b1,b0,c1,c0,zzeros,zpoles]=syredi(ityp,iapro,om,deltap,deltas)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>itype</term>
-                <listitem>
-                    <para>integer, the filter type: 1 stands for low-pass, 2 for
-                        high-pass, 3 for band-pass, 4 for stop-band.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>iappro</term>
-                <listitem>
-                    <para>integer, the design approximation type: 1 stands for
-                        butterworth, 2 for elliptic, 3 for Chebytchev1, 4 for
-                        Chebytchev2.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>om</term>
-                <listitem>
-                    <para>4-vector of cutoff frequencies (in radians)
-                        <literal>om=[om1,om2,om3,om4]</literal>, <literal/>
-                    </para>
-                    <para>
-                        <literal>0&lt;= om1 &lt;= om2 &lt;= om3 &lt;= om4 &lt;=
-                            pi
-                        </literal>
-                        .
-                    </para>
-                    <para>
-                        When <literal>ftype</literal>='lp' or <literal>'hp'</literal>,
-                        <literal>om3</literal> and <literal>om4</literal> are not used and
-                        may be set to 0.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>deltap</term>
-                <listitem>
-                    <para>
-                        a real scalar, the ripple in the passband. <literal>0&lt;
-                            deltap &lt;1
-                        </literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>deltas</term>
-                <listitem>
-                    <para>
-                        a real scalar, the ripple in the stopband. <literal>0&lt;
-                            deltas &lt;1
-                        </literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>gain</term>
-                <listitem>
-                    <para>scalar, the filter gain</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>b2</term>
-                <listitem>
-                    <para>real row vector, degree 2 coefficients of numerators.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>b1</term>
-                <listitem>
-                    <para>real row vector, degree 1 coefficients of numerators.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>b0</term>
-                <listitem>
-                    <para>real row vector, degree 0 coefficients of numerators.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>c1</term>
-                <listitem>
-                    <para>real row vector, degree 1 coefficients of denominators.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>c0</term>
-                <listitem>
-                    <para>real row vector, degree 0 coefficients of denominators.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zzeros</term>
-                <listitem>
-                    <para>complex row vector, filter zeros in the z-domain</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zpoles</term>
-                <listitem>
-                    <para>complex row vector, filter poles in the z-domain</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>Computes iir filter approximation. The result is given as a set of
-            second order transfer functions
-            <literal>Hi=(b0(i)+b1(i)*z+b2(i)*z^2)/(c0(i)+c1(i)*z+z^2)</literal> and
-            also as a poles, zeros, gain representation.
-        </para>
-        <para>
-            The filter obtained is <literal>h=fact*H1*...*Hn</literal>.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Remark</title>
-        <para>
-            This built-in function is mainly intended to be used by the <link linkend="eqiir">eqiir</link> function.
-        </para>
-    </refsection>
-    <refsection>
-        <title>References</title>
-        <para>The syredi code is derived from doredi package written by Guenter F.
-            Dehner, Institut fuer Nachrichtentechnik Universitaet Erlangen-Nuernberg,
-            Germany.
-        </para>
-        <para>Dehner,G.F. 1979, DOREDI: Program for Design and Optimization of
-            REcursive DIgital filters-Programs for Digital Signal Processing,
-            ed:Digital Signal Processing committee of IEEE Acoustics, Speech and
-            Signal Processing Society.
-        </para>
-        <para>For DOREDI.f source code see
-            http://michaelgellis.tripod.com/dsp/pgm25.html
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-[fact,b2,b1,b0,c1,c0,zzeros,zpoles]=syredi(1,4,[2*%pi/10,4*%pi/10,0,0],0.02,0.001);
-h=fact*(b0+b1*%z+b2*%z^2)./(c0+c1*%z+%z^2)
- ]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="eqiir">eqiir</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/system.xml b/scilab/modules/signal_processing/help/fr_FR/filters/system.xml
deleted file mode 100644 (file)
index f91a30d..0000000
+++ /dev/null
@@ -1,108 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="system">
-    <refnamediv>
-        <refname>system</refname>
-        <refpurpose>observation update</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[x1,y]=system(x0,f,g,h,q,r)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>x0</term>
-                <listitem>
-                    <para>input state vector</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>f</term>
-                <listitem>
-                    <para>system matrix</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>g</term>
-                <listitem>
-                    <para>input matrix</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>h</term>
-                <listitem>
-                    <para>Output matrix</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>q</term>
-                <listitem>
-                    <para>input noise covariance matrix</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>r</term>
-                <listitem>
-                    <para>output noise covariance matrix</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x1</term>
-                <listitem>
-                    <para>output state vector</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>y</term>
-                <listitem>
-                    <para>output observation</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            define system function which generates the next
-            observation given the old state.
-            System recursively calculated
-        </para>
-        <programlisting role=""><![CDATA[
-x1=f*x0+g*u
-y=h*x0+v
- ]]></programlisting>
-        <para>
-            where <literal>u</literal> is distributed <literal>N(0,q)</literal>
-            and <literal>v</literal> is distribute <literal>N(0,r)</literal>.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-// initialize state statistics
-// (mean and err. variance)
-m0=[10 10]';
-p0=[2 0;0 2];
-// create system
-f=[1.1 0.1;0 0.8];
-g=[1 0;0 1];
-h=[1 0;0 1];
-// noise statistics
-q=[.03 0.01;.01 0.03];
-r=2*eye(2);
-// initialize system process
-rand("seed",2);
-rand("normal");
-p0c=chol(p0);
-x0=m0+p0c'*rand(ones(m0));
-yt=[];
-//initialize kalman filter
-xke0=m0;pk0=p0;
-// initialize err. variance
-ecv=[pk0(1,1) pk0(2,2)]';
-[x1,y]=system(x0,f,g,h,q,r)
- ]]></programlisting>
-    </refsection>
-
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/trans.xml b/scilab/modules/signal_processing/help/fr_FR/filters/trans.xml
deleted file mode 100644 (file)
index bfad3a1..0000000
+++ /dev/null
@@ -1,163 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="trans">
-    <refnamediv>
-        <refname>trans</refname>
-        <refpurpose>low-pass to other filter transform</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>
-            hzt=trans(hz,tr_type,frq)
-            hzt=trans(pd,zd,gd,tr_type,frq)
-            [pt,zt,gt]=trans(hz,tr_type,frq)
-            [pt,zt,gt]=trans(pd,zd,gd,tr_type,frq)
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>hz</term>
-                <listitem>
-                    <para>a single input single output discrete transfer function, the low pass filter</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>pd</term>
-                <listitem>
-                    <para>Vector of given filter poles</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zd</term>
-                <listitem>
-                    <para>Vector of given filter zeros</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>gd</term>
-                <listitem>
-                    <para>scalar: the given filter gain</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>tr_type</term>
-                <listitem>
-                    <para>string, the type of transformation, see description for possible values </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>frq</term>
-                <listitem>
-                    <para>2-vector of discrete cut-off frequencies
-                        (i.e.,<literal>0&lt;frq&lt;.5</literal>). see description
-                        for details.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>hzt</term>
-                <listitem>
-                    <para>transformed filter transfert function.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>pt</term>
-                <listitem>
-                    <para>vector of transformed filter zeros.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zt</term>
-                <listitem>
-                    <para>vector of transformed filter poles.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>gt</term>
-                <listitem>
-                    <para>a scalar: transformed filter gain.</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>function for transforming standardized low-pass filter given its
-            poles-zeros_gain representation into
-            one of the following filters:
-        </para>
-        <variablelist>
-            <varlistentry>
-                <term>tr_type='lp'</term>
-                <listitem>
-                    <para>low pass filter, the cutoff frequency is given by the
-                        first entry of <literal>frq</literal>, the second one is ignored.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>tr_type='hp'</term>
-                <listitem>
-                    <para>high pass filter, the cutoff frequency is given by the
-                        first entry of  <literal>frq</literal>, the second one is ignored.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>tr_type='bp'</term>
-                <listitem>
-                    <para>
-                        band pass filter, the frequency range is given by <literal>frq(1)</literal> and <literal>frq(2)</literal>.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>tr_type='sb'</term>
-                <listitem>
-                    <para>
-                        stop band filter, the frequency range is given by <literal>frq(1)</literal> and <literal>frq(2)</literal>.
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Used functions</title>
-        <para>
-            <link linkend="bilt">bilt</link>
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-Hlp=iir(3,'lp','ellip',[0.1 0],[.08 .03]);
-Hbp=trans(Hlp,'bp',[0.01 0.1]);
-Hsb=trans(Hlp,'sb',[0.01 0.1])
-
-clf();gainplot([Hlp;Hbp;Hsb],1d-3,0.48);
-l=legend(['original low pass';'band pass';'stop band']);
-l.legend_location="in_lower_left";
- ]]></programlisting>
-        <scilab:image><![CDATA[
-Hlp=iir(3,'lp','ellip',[0.1 0],[.08 .03]);
-Hbp=trans(Hlp,'bp',[0.01 0.1]);
-Hsb=trans(Hlp,'sb',[0.01 0.1])
-
-clf();gainplot([Hlp;Hbp;Hsb],1d-3,0.48);
-l=legend(['original low pass';'band pass';'stop band']);
-l.legend_location="in_lower_left";
-]]>     </scilab:image>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="iir">iir</link>
-            </member>
-            <member>
-                <link linkend="bilt">bilt</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/wfir.xml b/scilab/modules/signal_processing/help/fr_FR/filters/wfir.xml
deleted file mode 100644 (file)
index 9a2bc79..0000000
+++ /dev/null
@@ -1,89 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook"  xml:lang="fr" xmlns:scilab="http://www.scilab.org" xml:id="wfir">
-    <refnamediv>
-        <refname>wfir</refname>
-        <refpurpose>linear-phase FIR filters</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[wft,wfm,fr]=wfir(ftype,forder,cfreq,wtype,fpar)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>ftype</term>
-                <listitem>
-                    <para>
-                        string : <literal>'lp','hp','bp','sb'</literal> (filter type)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>forder</term>
-                <listitem>
-                    <para>
-                        Filter order (pos integer)(odd for <literal>ftype='hp'</literal> or <literal>'sb'</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>cfreq</term>
-                <listitem>
-                    <para>
-                        2-vector of cutoff frequencies (<literal>0&lt;cfreq(1),cfreq(2)&lt;.5</literal>)  only <literal>cfreq(1)</literal> is used when <literal>ftype='lp'</literal> or <literal>'hp'</literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>wtype</term>
-                <listitem>
-                    <para>
-                        Window type (<literal>'re','tr','hm','hn','kr','ch'</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fpar</term>
-                <listitem>
-                    <para>
-                        2-vector of window parameters. Kaiser window <literal>fpar(1)&gt;0 fpar(2)=0</literal>. Chebyshev window  <literal>fpar(1)&gt;0, fpar(2)&lt;0</literal> or <literal>fpar(1)&lt;0, 0&lt;fpar(2)&lt;.5</literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>wft</term>
-                <listitem>
-                    <para>time domain filter coefficients</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>wfm</term>
-                <listitem>
-                    <para>frequency domain filter response on the grid fr</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fr</term>
-                <listitem>
-                    <para>Frequency grid</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Function which makes linear-phase, FIR low-pass, band-pass,
-            high-pass, and stop-band filters
-            using the windowing technique.
-            Works interactively if called with no arguments.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-[h,hm,fr]=wfir("lp",33,[.2 0],"hm",[0 0])
- ]]></programlisting>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/wfir_gui.xml b/scilab/modules/signal_processing/help/fr_FR/filters/wfir_gui.xml
deleted file mode 100644 (file)
index 6704a18..0000000
+++ /dev/null
@@ -1,114 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="en_US" xml:id="wfir_gui">
-    <refnamediv>
-        <refname>wfir_gui</refname>
-        <refpurpose>Graphical user interface that can be used to interactively design wfir filters</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[ftype,forder,cfreq,wtype,fpar] = wfir_gui()</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Parameters</title>
-        <variablelist>
-            <varlistentry>
-                <term>ftype</term>
-                <listitem>
-                    <para>
-                        a string: the selected filter type.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>forder</term>
-                <listitem>
-                    <para>
-                        a scalar with positive integer value: the selected filter order
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>cfreq</term>
-                <listitem>
-                    <para>
-                        a 2 vector: the cut-off frequencies in normalized frequencies
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>wtype</term>
-                <listitem>
-                    <para>
-                        a string: the selected window type.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fpar</term>
-                <listitem>
-                    <para>
-                        2-vector of window parameters.
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            This function proposes a graphical user interface to allow user
-            interactively select the design parameters of windowed
-            finite impulse response filters (see <link linkend="wfir">wfir</link>). It is called by
-            <literal>wfir</literal> when no input arguments are given.
-        </para>
-        <para>
-            <inlinemediaobject>
-                <imageobject>
-                    <imagedata fileref="../../images/wfir_gui_dialog.png"/>
-                </imageobject>
-            </inlinemediaobject>
-        </para>
-        <para>
-            If requested, the frequency response of the filter is
-            automatically updated according to the parameters set in the
-            dialog window:
-        </para>
-        <para>
-            <inlinemediaobject>
-                <imageobject>
-                    <imagedata fileref="../../images/wfir_gui_view.svg"/>
-                </imageobject>
-            </inlinemediaobject>
-        </para>
-    </refsection>
-    <refsection>
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="wfir">wfir</link>
-            </member>
-        </simplelist>
-    </refsection>
-    <refsection>
-        <title>Used Functions</title>
-        <para>
-            Based on <link linkend="uicontrol">uicontrol</link> functions.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-wfir_gui()
- ]]></programlisting>
-    </refsection>
-
-    <refsection>
-        <title>History</title>
-        <revhistory>
-            <revision>
-                <revnumber>5.4.0</revnumber>
-                <revremark>Function wfir_gui is redesigned from scratch to provide a better user experience.</revremark>
-            </revision>
-        </revhistory>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/wiener.xml b/scilab/modules/signal_processing/help/fr_FR/filters/wiener.xml
deleted file mode 100644 (file)
index 577273a..0000000
+++ /dev/null
@@ -1,252 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org"   xml:lang="fr" xml:id="wiener">
-    <refnamediv>
-        <refname>wiener</refname>
-        <refpurpose>Wiener estimate</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[xs,ps,xf,pf]=wiener(y,x0,p0,f,g,h,q,r)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>f, g, h</term>
-                <listitem>
-                    <para>
-                        system matrices in the interval <literal>[t0,tf]</literal>
-                    </para>
-                    <variablelist>
-                        <varlistentry>
-                            <term>f</term>
-                            <listitem>
-                                <para>
-                                    =<literal>[f0,f1,...,ff]</literal>, and <literal>fk</literal> is a nxn matrix
-                                </para>
-                            </listitem>
-                        </varlistentry>
-                        <varlistentry>
-                            <term>g</term>
-                            <listitem>
-                                <para>
-                                    =<literal>[g0,g1,...,gf]</literal>, and <literal>gk</literal> is a nxn matrix
-                                </para>
-                            </listitem>
-                        </varlistentry>
-                        <varlistentry>
-                            <term>h</term>
-                            <listitem>
-                                <para>
-                                    =<literal>[h0,h1,...,hf]</literal>, and <literal>hk</literal> is a mxn matrix
-                                </para>
-                            </listitem>
-                        </varlistentry>
-                    </variablelist>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>q, r</term>
-                <listitem>
-                    <para>covariance matrices of dynamics and observation noise</para>
-                    <variablelist>
-                        <varlistentry>
-                            <term>q</term>
-                            <listitem>
-                                <para>
-                                    =<literal>[q0,q1,...,qf]</literal>, and <literal>qk</literal> is a nxn matrix
-                                </para>
-                            </listitem>
-                        </varlistentry>
-                        <varlistentry>
-                            <term>r</term>
-                            <listitem>
-                                <para>
-                                    =<literal>[r0,r1,...,rf]</literal>, and <literal>gk</literal> is a mxm matrix
-                                </para>
-                            </listitem>
-                        </varlistentry>
-                    </variablelist>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x0, p0</term>
-                <listitem>
-                    <para>initial state estimate and error variance</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>y</term>
-                <listitem>
-                    <para>
-                        observations in the interval <literal>[t0,tf]</literal>. <literal>y=[y0,y1,...,yf]</literal>, and <literal>yk</literal> is a column m-vector
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>xs</term>
-                <listitem>
-                    <para>
-                        Smoothed state estimate <literal>xs= [xs0,xs1,...,xsf]</literal>, and <literal>xsk</literal> is a column n-vector
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>ps</term>
-                <listitem>
-                    <para>
-                        Error covariance of smoothed estimate <literal>ps=[p0,p1,...,pf]</literal>, and <literal>pk</literal> is a nxn matrix
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>xf</term>
-                <listitem>
-                    <para>
-                        Filtered state estimate <literal>xf= [xf0,xf1,...,xff]</literal>, and <literal>xfk</literal> is a column n-vector
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>pf</term>
-                <listitem>
-                    <para>
-                        Error covariance of filtered estimate <literal>pf=[p0,p1,...,pf]</literal>, and <literal>pk</literal> is a nxn matrix
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            function which gives the Wiener estimate using
-            the forward-backward Kalman filter formulation
-        </para>
-    </refsection>
-    <refsection>
-        <title>Sample</title>
-        <scilab:image>
-            m0=[10 10]';
-            p0=[100 0;0 100];
-            f2=[1.1 50.1;0 0.8];
-            g=[1 0;0 1];
-            h=[1 0;0 1];
-            [hi,hj]=size(h);
-            q=[.01 0;0 0.01];
-            r=20*eye(2,2);
-            rand("seed",66);
-            rand("normal");
-            p0c=chol(p0);
-            x0=m0+p0c'*rand(ones(m0));
-            y=h*x0+chol(r)'*rand(ones(1:hi))';
-            yt=y;
-            x=x0;
-            ft=[f2];
-            gt=[g];
-            ht=[h];
-            qt=[q];
-            rt=[r];
-            n=10;
-            for k=1:n
-            [x1,y]=system(x0,f2,g,h,q,r);
-            x=[x x1];
-            yt=[yt y];
-            x0=x1;
-            ft=[ft f2];
-            gt=[gt g];
-            ht=[ht h];
-            qt=[qt q];
-            rt=[rt r];
-            end
-            [xs,ps,xf,pf]=wiener(yt,m0,p0,ft,gt,ht,qt,rt);
-            a=min([x(1,:)-2*sqrt(ps(1,1:2:2*(n+1))),xf(1,:),xs(1,:)]);
-            b=max([x(1,:)+2*sqrt(ps(1,1:2:2*(n+1))),xf(1,:),xs(1,:)]);
-            c=min([x(2,:)-2*sqrt(ps(2,2:2:2*(n+1))),xf(2,:),xs(2,:)]);
-            d=max([x(2,:)+2*sqrt(ps(2,2:2:2*(n+1))),xf(2,:),xs(2,:)]);
-            xmargin=max([abs(a),abs(b)]);
-            ymargin=max([abs(c),abs(d)]);
-            a=-0.1*xmargin+a;
-            b=.1*xmargin+b;
-            c=-0.1*ymargin+c;
-            d=.1*ymargin+d;
-            scf();
-            plot([a a b],[d c c]);
-            plot2d(x(1,:)',x(2,:)',[2],"000")
-            plot2d(xf(1,:)',xf(2,:)',[2],"000")
-            plot2d(xs(1,:)',xs(2,:)',[2],"000")
-            plot2d(xs(1,:)',xs(2,:)',[-2],"000")
-            plot2d(xf(1,:)',xf(2,:)',[-3],"000")
-            plot2d(x(1,:)',x(2,:)',[-4],"000")
-        </scilab:image>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-// initialize state statistics (mean and er. variance)
-m0=[10 10]';
-p0=[100 0;0 100];
-// create system
-f2=[1.1 50.1;0 0.8];
-g=[1 0;0 1];
-h=[1 0;0 1];
-[hi,hj]=size(h);
-// noise statistics
-q=[.01 0;0 0.01];
-r=20*eye(2,2);
-// initialize system process
-rand("seed",66);
-rand("normal");
-p0c=chol(p0);
-x0=m0+p0c'*rand(ones(m0));
-y=h*x0+chol(r)'*rand(ones(1:hi))';
-yt=y;
-// initialize plotted variables
-x=x0;
-// loop
-ft=[f2];
-gt=[g];
-ht=[h];
-qt=[q];
-rt=[r];
-n=10;
-for k=1:n
-    // generate the state and observation
-    // at time k (i.e. xk and yk)
-    [x1,y]=system(x0,f2,g,h,q,r);
-    x=[x x1];
-    yt=[yt y];
-    x0=x1;
-    ft=[ft f2];
-    gt=[gt g];
-    ht=[ht h];
-    qt=[qt q];
-    rt=[rt r];
-end
-// get the wiener filter estimate
-[xs,ps,xf,pf]=wiener(yt,m0,p0,ft,gt,ht,qt,rt);
-// plot result
-a=min([x(1,:)-2*sqrt(ps(1,1:2:2*(n+1))),xf(1,:),xs(1,:)]);
-b=max([x(1,:)+2*sqrt(ps(1,1:2:2*(n+1))),xf(1,:),xs(1,:)]);
-c=min([x(2,:)-2*sqrt(ps(2,2:2:2*(n+1))),xf(2,:),xs(2,:)]);
-d=max([x(2,:)+2*sqrt(ps(2,2:2:2*(n+1))),xf(2,:),xs(2,:)]);
-xmargin=max([abs(a),abs(b)]);
-ymargin=max([abs(c),abs(d)]);
-a=-0.1*xmargin+a;
-b=.1*xmargin+b;
-c=-0.1*ymargin+c;
-d=.1*ymargin+d;
-// plot frame, real state (x), and estimates (xf, and xs)
-scf();
-plot([a a b],[d c c]);
-plot2d(x(1,:)',x(2,:)',[2],"000")
-plot2d(xf(1,:)',xf(2,:)',[2],"000")
-plot2d(xs(1,:)',xs(2,:)',[2],"000")
-// mark data points (* for real data, o for estimates)
-plot2d(xs(1,:)',xs(2,:)',[-2],"000")
-plot2d(xf(1,:)',xf(2,:)',[-3],"000")
-plot2d(x(1,:)',x(2,:)',[-4],"000")
- ]]></programlisting>
-    </refsection>
-
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/wigner.xml b/scilab/modules/signal_processing/help/fr_FR/filters/wigner.xml
deleted file mode 100644 (file)
index eed270a..0000000
+++ /dev/null
@@ -1,96 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org"   xml:lang="fr" xml:id="wigner">
-    <refnamediv>
-        <refname>wigner</refname>
-        <refpurpose>'time-frequency' wigner spectrum</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[tab]=wigner(x,h,deltat,zp)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>tab</term>
-                <listitem>
-                    <para>wigner spectrum (lines correspond to the time variable)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>x</term>
-                <listitem>
-                    <para>analyzed signal</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>h</term>
-                <listitem>
-                    <para>data window</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>deltat</term>
-                <listitem>
-                    <para>analysis time increment (in samples)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zp</term>
-                <listitem>
-                    <para>
-                        length of FFT's. <literal>%pi/zp</literal> gives the frequency increment.
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            function which computes the 'time-frequency' wigner
-            spectrum of a signal.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Sample</title>
-        <scilab:image>
-            a=[488^2 488 1;408^2 408 1;568^2 568 1];
-            b=[1.28;0;0];
-            x=a\b;
-            t=408:568;
-            p=x'*[t.*t;t;ones(t)];
-            u=[0*ones(408:487) ones(488:568)];
-            s=p.*sin(2*%pi/16*t+u*%pi);
-            s=[0*ones(0:407) s 0*ones(569:951)];
-            h=ones(1,64);
-            w=wigner(s,h,12,128);
-            scf();
-            plot3d(1:69,1:64,abs(w(1:69,1:64)));
-        </scilab:image>
-    </refsection>
-
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-a=[488^2 488 1;408^2 408 1;568^2 568 1];
-b=[1.28;0;0];
-x=a\b;
-t=408:568;
-p=x'*[t.*t;t;ones(t)];
-// unit step function
-u=[0*ones(408:487) ones(488:568)];
-// finite duration sinusoid
-s=p.*sin(2*%pi/16*t+u*%pi);
-// signal to be analyzed
-s=[0*ones(0:407) s 0*ones(569:951)];
-// 64-point rectangular window
-h=ones(1,64);
-// wigner spectrum
-w=wigner(s,h,12,128);
-scf();
-plot3d(1:69,1:64,abs(w(1:69,1:64)));
- ]]></programlisting>
-    </refsection>
-
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/window.xml b/scilab/modules/signal_processing/help/fr_FR/filters/window.xml
deleted file mode 100644 (file)
index e5afd3d..0000000
+++ /dev/null
@@ -1,296 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook"  xml:lang="fr" xmlns:scilab="http://www.scilab.org" xml:id="window">
-    <refnamediv>
-        <refname>window</refname>
-        <refpurpose>compute symmetric window of various type</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>win_l=window('re',n)
-            win_l=window('tr',n)
-            win_l=window('hn',n)
-            win_l=window('hm',n)
-            win_l=window('kr',n,Beta)
-            [win_l,cwp]=window('ch',n,par)
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>window length</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>par</term>
-                <listitem>
-                    <para>
-                        parameter 2-vector <literal>par=[dp,df])</literal>, where
-                        <literal>dp</literal>  (<literal>0&lt;dp&lt;.5</literal>) rules the  main lobe
-                        width and  <literal>df</literal> rules the side lobe height
-                        (<literal>df&gt;0</literal>).
-                    </para>
-                    <para>Only one of these two value should be specified, the other one
-                        must be equal to a nonpositive value.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>Beta</term>
-                <listitem>
-                    <para>
-                        Kaiser window parameter <literal>Beta &gt;0</literal>).
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>win</term>
-                <listitem>
-                    <para>window</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>cwp</term>
-                <listitem>
-                    <para>unspecified Chebyshev window parameter</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            function which calculates various symmetric window for Digital signal processing.
-        </para>
-        <itemizedlist>
-            <listitem>
-                <para>
-                    The Kaiser window is a nearly optimal window function. <literal>Beta</literal>
-                    is an arbitrary positive real number that determines the shape of the
-                    window,  and the integer  <literal>n</literal> is the length of the window.
-                </para>
-                <para>
-                    By construction, this function peaks at unity for <literal> k = n/2</literal> ,
-                    i.e. at the center of the window, and decays exponentially towards the
-                    window edges.   The larger the value of <literal>Beta</literal>, the narrower
-                    the window becomes; <literal>Beta = 0</literal> corresponds to a rectangular window.
-                    Conversely, for larger <literal>Beta</literal> the width of the main lobe
-                    increases in the Fourier transform, while the side lobes decrease in
-                    amplitude.
-                    Thus, this parameter controls the tradeoff between main-lobe width and
-                    side-lobe area.
-                </para>
-                <informaltable border="1">
-                    <tr>
-                        <td>Beta</td>
-                        <td>window shape</td>
-                    </tr>
-                    <tr>
-                        <td>0</td>
-                        <td>Rectangular shape</td>
-                    </tr>
-                    <tr>
-                        <td>5</td>
-                        <td>Similar to the Hamming window</td>
-                    </tr>
-                    <tr>
-                        <td>6</td>
-                        <td>Similar to the Hann window</td>
-                    </tr>
-                    <tr>
-                        <td>8.6</td>
-                        <td>Similar to the Blackman window</td>
-                    </tr>
-                </informaltable>
-            </listitem>
-            <listitem>
-                <para>
-                    The Chebyshev window minimizes the mainlobe width, given a particular sidelobe
-                    height. It is characterized by an equiripple behavior, that is, its
-                    sidelobes all have the same height.
-                </para>
-            </listitem>
-            <listitem>
-                <para>
-                    The Hann and Hamming windows are quite similar, they only differ in
-                    the choice of one parameter <literal>alpha</literal>:
-                    <literal> w=alpha+(1 - alpha)*cos(2*%pi*x/(n-1))</literal>
-                    <literal>alpha</literal> is equal to 1/2 in Hann window and to 0.54 in
-                    Hamming window.
-                </para>
-            </listitem>
-        </itemizedlist>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-    clf()
-    N = 24;
-    whm = window('hm', N); // Hamming window
-    wkr = window('kr', N, 6); // Hamming Kaiser window
-    wch = window('ch', N, [0.005 -1]); // Chebychev window
-
-    // Plot the window profile
-    subplot(121);
-    plot((1:N)', [whm; wkr; wch]')
-    set(gca(), 'grid', [1 1]*color('gray'))
-    xlabel("n")
-    ylabel("w_n")
-    title(gettext("Profile plot"))
-
-    // Plot the magnitude of the frequency responses
-    n = 256;
-    [Whm,fr] = frmag(whm, n);
-    [Wkr,fr] = frmag(wkr, n);
-    [Wch,fr] = frmag(wch, n);
-    subplot(122);
-    plot(fr', 20*log10([Whm; Wkr; Wch]'))
-    set(gca(), 'grid', [1 1]*color('gray'))
-    xlabel(gettext("Pulsation (rad/s)"))
-    ylabel(gettext("Magnitude (dB)"))
-    legend(["Hamming N=24"; "Kaiser N=24, Beta=6"; "Chebychev N=24, dp=0.005"]);
-    title(gettext("Magnitude plot"))
-    ]]></programlisting>
-        <para>
-            <scilab:image>
-                clf()
-                N=24;
-                whm=window('hm',N);//Hamming window
-                wkr=window('kr',N,6);//Hamming Kaiser window
-                wch=window('ch',N,[0.005,-1]);//Chebychev window
-                //plot the window profile
-                subplot(121);plot((1:N)',[whm;wkr;wch]')
-                set(gca(),'grid',[1 1]*color('gray'))
-                xlabel("n")
-                ylabel("w_n")
-                title(gettext("Profile plot"))
-                //plot the magnitude of the frequency responses
-                n=256;
-                [Whm,fr]=frmag(whm,n);
-                [Wkr,fr]=frmag(wkr,n);
-                [Wch,fr]=frmag(wch,n);
-                subplot(122);plot(fr',20*log10([Whm;Wkr;Wch]'))
-                set(gca(),'grid',[1 1]*color('gray'))
-                xlabel(gettext("Pulsation (rad/s)"))
-                ylabel(gettext("Magnitude (dB)"))
-                legend(["Hamming N=24";"Kaiser N=24, Beta=6";"Chebychev N=24, dp=0.005"]);
-                title(gettext("Magnitude plot"))
-            </scilab:image>
-        </para>
-        <programlisting role="example"><![CDATA[
-    clf()
-    N = 140;
-    w1 = window('kr', N, 1);
-    w2 = window('kr', N, 2);
-    w4 = window('kr', N, 4);
-    w8 = window('kr', N, 8);
-    w16 = window('kr', N, 16);
-
-    // Plot the window profile
-    plot((1:N)', [w1; w2; w4; w8; w16]')
-    set(gca(), 'grid', [1 1]*color('gray'))
-    legend("$\beta = "+string([1;2;4;8;16])+'$',[55,0.3])
-    xlabel("n")
-    ylabel("w_n")
-    title(gettext("Comparison of Kaiser window profiles"))
-    ]]></programlisting>
-        <para>
-            <scilab:image>
-                clf()
-                N=140;
-                w1=window('kr',N,1);
-                w2=window('kr',N,2);
-                w4=window('kr',N,4);
-                w8=window('kr',N,8);
-                w16=window('kr',N,16);
-
-                //plot the window profile
-                plot((1:N)',[w1;w2;w4;w8;w16]')
-                set(gca(),'grid',[1 1]*color('gray'))
-                legend("$\beta="+string([1;2;4;8;16])+'$',[55,0.3])
-                xlabel("n")
-                ylabel("w_n")
-                title(gettext("Comparison of Kaiser window profiles"))
-            </scilab:image>
-        </para>
-        <programlisting role="example"><![CDATA[
-    clf()
-    N = 140;
-    w1 = window('ch', N, [0.001 -1]);
-    w2 = window('ch', N, [0.05 -1]);
-    w3 = window('ch', N, [-1 0.4]);
-
-    // Plot the window profile
-    subplot(121);
-    plot((1:N)', [w1; w2; w3]')
-    set(gca(), 'grid', [1 1]*color('gray'))
-    //legend("$\beta = "+string([1;2;4;8;16])+'$',[55,0.3])
-    xlabel("n")
-    ylabel("w_n")
-    title(gettext("Comparison of Chebychev window profiles"))
-
-    // Plot the magnitude of the frequency responses
-    n = 256;
-    [W1,fr] = frmag(w1, n);
-    [W2,fr] = frmag(w2, n);
-    [W3,fr] = frmag(w3, n);
-    subplot(122);
-    plot(fr', 20*log10([W1; W2; W3]'))
-    set(gca(), 'grid', [1 1]*color('gray'))
-    xlabel(gettext("Pulsation (rad/s)"))
-    ylabel(gettext("Magnitude (dB)"))
-    legend(["Chebychef dp=0.001"; "Chebychef dp=0.05"; "Chebychef df=0.4"]);
-    title(gettext("Chebychev window Magnitude plot"))
-    ]]></programlisting>
-        <para>
-            <scilab:image>
-                N=140;
-                w1=window('ch',N,[0.001,-1]);
-                w2=window('ch',N,[0.05,-1]);
-                w3=window('ch',N,[-1,0.4]);
-
-                //plot the window profile
-                subplot(121);plot((1:N)',[w1;w2;w3]')
-                set(gca(),'grid',[1 1]*color('gray'))
-                //legend("$\beta="+string([1;2;4;8;16])+'$',[55,0.3])
-                xlabel("n")
-                ylabel("w_n")
-                title(gettext("Comparison of Chebychev window profiles"))
-                //plot the magnitude of the frequency responses
-                n=256;
-                [W1,fr]=frmag(w1,n);
-                [W2,fr]=frmag(w2,n);
-                [W3,fr]=frmag(w3,n);
-                subplot(122);plot(fr',20*log10([W1;W2;W3]'))
-                set(gca(),'grid',[1 1]*color('gray'))
-                xlabel(gettext("Pulsation (rad/s)"))
-                ylabel(gettext("Magnitude (dB)"))
-                legend(["Chebychef dp=0.001";"Chebychef dp=0.05";"Chebychef df=0.4"]);
-                title(gettext("Chebychev window Magnitude plot"))
-            </scilab:image>
-
-        </para>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="wfir">wfir</link>
-            </member>
-            <member>
-                <link linkend="frmag">frmag</link>
-            </member>
-            <member>
-                <link linkend="ffilt">ffilt</link>
-            </member>
-        </simplelist>
-    </refsection>
-    <refsection>
-        <title>Bibliography</title>
-        <para>IEEE. Programs for Digital Signal Processing. IEEE Press. New York: John
-            Wiley and Sons, 1979. Program 5.2.
-        </para>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/yulewalk.xml b/scilab/modules/signal_processing/help/fr_FR/filters/yulewalk.xml
deleted file mode 100644 (file)
index 81e94d1..0000000
+++ /dev/null
@@ -1,103 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="yulewalk">
-    <refnamediv>
-        <refname>yulewalk</refname>
-        <refpurpose>least-square filter design</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>Hz = yulewalk(N,frq,mag)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>N</term>
-                <listitem>
-                    <para>integer (order of desired filter)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>frq</term>
-                <listitem>
-                    <para>real row vector (non-decreasing order), frequencies.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>mag</term>
-                <listitem>
-                    <para>non negative real row vector (same size as frq), desired magnitudes.</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>Hz</term>
-                <listitem>
-                    <para>
-                        filter <literal>B(z)/A(z)</literal>
-                    </para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Hz = yulewalk(N,frq,mag) finds the N-th order iir filter
-        </para>
-        <programlisting role="no-scilab-exec"><![CDATA[
-                  n-1         n-2
-      B(z)   b(1)z     + b(2)z    + .... + b(n)
-H(z)= ---- = ---------------------------------
-                n-1       n-2
-      A(z)    z   + a(2)z    + .... + a(n)
- ]]></programlisting>
-        <para>
-            which matches the magnitude frequency response given by vectors frq and mag.
-            Vectors frq and mag specify the frequency and magnitude of the desired
-            frequency response. The frequencies in frq must be between 0.0 and 1.0,
-            with 1.0 corresponding to half the sample rate. They must be in
-            increasing order and start with 0.0 and end with 1.0.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-f=[0,0.4,0.4,0.6,0.6,1];
-H=[0,0,1,1,0,0];
-Hz=yulewalk(8,f,H);
-fs=1000;
-fhz = f*fs/2;
-scf(0);
-clf
-plot2d(fhz',H');
-xtitle('Desired Frequency Response (Magnitude)')
-[frq,repf]=repfreq(Hz,0:0.001:0.5);
-scf(1);
-clf
-plot2d(fs*frq',abs(repf'));
-xtitle('Obtained Frequency Response (Magnitude)')
- ]]></programlisting>
-        <scilab:image>
-            f=[0,0.4,0.4,0.6,0.6,1];
-            H=[0,0,1,1,0,0];
-            Hz=yulewalk(8,f,H);
-            fs=1000;
-            fhz = f*fs/2;
-            scf(0);
-            clf
-            plot2d(fhz',H');
-            xtitle('Desired Frequency Response (Magnitude)')
-            [frq,repf]=repfreq(Hz,0:0.001:0.5);
-        </scilab:image>
-        <scilab:image>
-            f=[0,0.4,0.4,0.6,0.6,1];
-            H=[0,0,1,1,0,0];
-            Hz=yulewalk(8,f,H);
-            fs=1000;
-            fhz = f*fs/2;
-            [frq,repf]=repfreq(Hz,0:0.001:0.5);
-            plot2d(fs*frq',abs(repf'));
-            xtitle('Obtained Frequency Response (Magnitude)')
-        </scilab:image>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/zpbutt.xml b/scilab/modules/signal_processing/help/fr_FR/filters/zpbutt.xml
deleted file mode 100644 (file)
index 690b605..0000000
+++ /dev/null
@@ -1,57 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="zpbutt">
-    <refnamediv>
-        <refname>zpbutt</refname>
-        <refpurpose>Butterworth analog filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[pols,gain]=zpbutt(n,omegac)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>integer (filter order)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>omegac</term>
-                <listitem>
-                    <para>real (cut-off angular frequency in radians per second)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>pols</term>
-                <listitem>
-                    <para>resulting poles of filter</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>gain</term>
-                <listitem>
-                    <para>resulting gain of filter</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            computes the poles of a Butterworth analog
-            filter of order <literal>n</literal> and cutoff frequency omegac
-            transfer function H(s) is calculated by <literal>H(s)=gain/real(poly(pols,'s'))</literal>
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-n=7;
-omegac=3;
-[pols,gain]=zpbutt(n,omegac)
- ]]></programlisting>
-    </refsection>
-
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/zpch1.xml b/scilab/modules/signal_processing/help/fr_FR/filters/zpch1.xml
deleted file mode 100644 (file)
index cc09a07..0000000
+++ /dev/null
@@ -1,67 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="zpch1">
-    <refnamediv>
-        <refname>zpch1</refname>
-        <refpurpose>Chebyshev analog filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[poles,gain]=zpch1(n,epsilon,omegac)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>integer (filter order)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>epsilon</term>
-                <listitem>
-                    <para>
-                        real : ripple in the pass band (<literal>0&lt;epsilon&lt;1</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>omegac</term>
-                <listitem>
-                    <para>real : cut-off angular frequency in radians per second</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>poles</term>
-                <listitem>
-                    <para>resulting filter poles</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>gain</term>
-                <listitem>
-                    <para>resulting filter gain</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Poles of a Type 1 Chebyshev analog filter. The transfer function is given by :
-        </para>
-        <programlisting role="no-scilab-exec"><![CDATA[
-H(s)=gain/poly(poles,'s')
- ]]></programlisting>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-n = 13;
-epsilon = 0.2;
-omegac = 3;
-[p,gain] = zpch1(n,epsilon,omegac)
- ]]></programlisting>
-    </refsection>
-
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/zpch2.xml b/scilab/modules/signal_processing/help/fr_FR/filters/zpch2.xml
deleted file mode 100644 (file)
index daec902..0000000
+++ /dev/null
@@ -1,74 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="zpch2">
-    <refnamediv>
-        <refname>zpch2</refname>
-        <refpurpose>Chebyshev analog filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[zeros,poles,gain]=zpch2(n,A,omegar)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>integer : filter order</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>A</term>
-                <listitem>
-                    <para>
-                        real : attenuation in stop band (<literal>A&gt;1</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>omegar</term>
-                <listitem>
-                    <para>real : cut-off angular frequency in radians per second</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zeros</term>
-                <listitem>
-                    <para>resulting filter zeros</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>poles</term>
-                <listitem>
-                    <para>resulting filter poles</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>gain</term>
-                <listitem>
-                    <para>Resulting filter gain</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Poles and zeros of a type 2 Chebyshev analog filter
-            gain is the gain of the filter
-        </para>
-        <programlisting role="no-scilab-exec"><![CDATA[
-H(s)=gain*poly(zeros,'s')/poly(poles,'s')
- ]]></programlisting>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-n=10;
-A=1/0.2;
-omegar=6;
-[z,p,gain]=zpch2(n,A,omegar)
- ]]></programlisting>
-    </refsection>
-
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/filters/zpell.xml b/scilab/modules/signal_processing/help/fr_FR/filters/zpell.xml
deleted file mode 100644 (file)
index 9bdd8da..0000000
+++ /dev/null
@@ -1,80 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="zpell">
-    <refnamediv>
-        <refname>zpell</refname>
-        <refpurpose>lowpass elliptic filter</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[zeros,poles,gain]=zpell(epsilon,A,omegac,omegar)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>epsilon</term>
-                <listitem>
-                    <para>
-                        real : ripple of filter in pass band (<literal>0&lt;epsilon&lt;1</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>A</term>
-                <listitem>
-                    <para>
-                        real : attenuation of filter in stop band (<literal>A&gt;1</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>omegac</term>
-                <listitem>
-                    <para>real : pass band cut-off angular frequency in radians per second</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>omegar</term>
-                <listitem>
-                    <para>real : stop band cut-off angular frequency in radians per second</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>zeros</term>
-                <listitem>
-                    <para>resulting zeros of filter</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>poles</term>
-                <listitem>
-                    <para>resulting poles of filter</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>gain</term>
-                <listitem>
-                    <para>resulting gain of filter</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Poles and zeros of prototype lowpass elliptic filter.
-            <literal>gain</literal> is the gain of the filter
-        </para>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="ell1mag">ell1mag</link>
-            </member>
-            <member>
-                <link linkend="eqiir">eqiir</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/howto/DesignEllipticFilter.xml b/scilab/modules/signal_processing/help/fr_FR/howto/DesignEllipticFilter.xml
deleted file mode 100644 (file)
index e3f9e11..0000000
+++ /dev/null
@@ -1,290 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xi="http://www.w3.org/2001/XInclude" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:html="http://www.w3.org/1999/xhtml" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:id="DesignEllipticFilter">
-    <refnamediv>
-        <refname>How to design an elliptic filter</refname>
-        <refpurpose>How to design an elliptic filter (analog and
-            digital)
-        </refpurpose>
-    </refnamediv>
-    <refsection>
-        <title>Description</title>
-        <para>The goal is to design a simple analog and digital elliptic
-            filter.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Designing an analog elliptic filter</title>
-        <para>There are several possibilities to design an elliptic lowpass
-            filter. We can use <link linkend="analpf">analpf</link> or <link linkend="zpell">zpell</link>. We will use zpell to produce the poles and
-            zeros of the filter. Once we have got these poles and zeros, we will have
-            to translate this representation into a <link linkend="syslin">syslin</link> one.
-        </para>
-        <para>And then, the filter can be represented in bode plot.</para>
-        <programlisting role=""><![CDATA[
-// analog elliptic (Bessel), order 2, cutoff 1 Hz
-Epsilon = 3;  // ripple of filter in pass band (0<epsilon<1)
-A       = 60; // attenuation of filter in stop band (A<1)
-OmegaC  = 10; // pass band cut-off frequency in Hertz
-OmegaR  = 50; // stop band cut-off frequency in Hertz
-
-// Generate the filter
-[_zeros,pols,gain] = zpell(3,60,10,50);
-
-// Generate the equivalent linear system of the filter
-num   = gain * real(poly(_zeros,'s'));;
-den   = real(poly(pols,'s'));
-elatf = syslin('c',num,den);
-
-// Plot the resulting filter
-bode(elatf,0.01,100);
-title('Analog Elliptic filter');
- ]]></programlisting>
-        <para>Bode plot is only suited for analog filters.</para>
-        <mediaobject>
-            <imageobject>
-                <imagedata align="center" fileref="../../images/analog_elliptic_filter.png"/>
-            </imageobject>
-        </mediaobject>
-        <para>If you want to design a highpass, bandpass or bandstop filter, you
-            can first design a lowpass and then transform this lowpass filter using
-            the <link linkend="trans">trans</link> function.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Designing a digital elliptic filter</title>
-        <para>Now, let's focus on how to produce a digital lowpass elliptic
-            filter.
-        </para>
-        <para>We can produce two kinds of digital filters:</para>
-        <itemizedlist>
-            <listitem>
-                <para>an IIR (Infinite Impulse Response).</para>
-                <para>To compute such a filter, we can use the following
-                    functions:
-                </para>
-                <itemizedlist>
-                    <listitem>
-                        <para>
-                            <link linkend="iir">iir</link>
-                        </para>
-                    </listitem>
-                    <listitem>
-                        <para>
-                            <link linkend="eqiir">eqiir</link>
-                        </para>
-                    </listitem>
-                </itemizedlist>
-            </listitem>
-            <listitem>
-                <para>a FIR (Finite Impulse Response).</para>
-                <para>To compute such a filter, we can use the following
-                    functions:
-                </para>
-                <itemizedlist>
-                    <listitem>
-                        <para>
-                            <link linkend="eqfir">eqfir</link>
-                        </para>
-                    </listitem>
-                    <listitem>
-                        <para>
-                            <link linkend="ffilt">ffilt</link>
-                        </para>
-                    </listitem>
-                    <listitem>
-                        <para>
-                            <link linkend="wfir">wfir</link>
-                        </para>
-                    </listitem>
-                    <listitem>
-                        <para>
-                            <link linkend="fsfirlin">fsfirlin</link>
-                        </para>
-                    </listitem>
-                </itemizedlist>
-            </listitem>
-        </itemizedlist>
-        <para>
-            For our demonstration, we will use the <link linkend="iir">iir</link> function.
-        </para>
-        <programlisting role="example"><![CDATA[
-Order   = 2; // The order of the filter
-Fs      = 1000; // The sampling frequency
-Fcutoff = 40;   // The cutoff frequency
-
-// We design a low pass elliptic filter
-hz = iir(Order,'lp','ellip',[Fcutoff/Fs/2 0],[0.1 0.1]);
-
-// We compute the frequency response of the filter
-[frq,repf]=repfreq(hz,0:0.001:0.5);
-[db_repf, phi_repf] = dbphi(repf);
-
-// And plot the bode like representation of the digital filter
-subplot(2,1,1);
-plot2d(Fs*frq,db_repf);
-xtitle('Obtained Frequency Response (Magnitude)');
-subplot(2,1,2);
-plot2d(Fs*frq,phi_repf);
-xtitle('Obtained Frequency Response (Phase in degree)');
- ]]></programlisting>
-        <para>Here is the representation of the digital elliptic filter.</para>
-        <mediaobject>
-            <imageobject>
-                <imagedata align="center" fileref="../../images/digital_elliptic_filter.png"/>
-            </imageobject>
-        </mediaobject>
-        <para>To represent the filter in phase and magnitude, we need first to
-            convert the discrete impulse response into magnitude and phase using the
-            <link linkend="dbphi">dbphi</link> function. This conversion is done using
-            a set of normalized frequencies.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Filtering a signal using the digital filter</title>
-        <para>Designing a filter is a first step. Once done, this filter will be
-            used to transform a signal. To get rid of some noise for example.
-        </para>
-        <para>In the following examples, we will filter a gaussian noise.</para>
-        <programlisting role=""><![CDATA[
-rand('normal');
-Input = rand(1,1000); // Produce a random gaussian noise
-t     = 1:1000;
-
-sl= tf2ss(hz); // From transfert function to syslin representation
-y = flts(Input,sl); // Filter the signal
-
-subplot(2,1,1);
-plot(t,Input);
-xtitle('The gaussian noise','t','y');
-subplot(2,1,2);
-plot(t,y);
-xtitle('The filtered gaussian noise','t','y');
- ]]></programlisting>
-        <para>Here is the representation of the signal before and after
-            filtering.
-        </para>
-        <mediaobject>
-            <imageobject>
-                <imagedata fileref="../../images/digital_filtered_noise.png"/>
-            </imageobject>
-        </mediaobject>
-        <para>As we can see in the result, the high frequencies of the noise have
-            been removed and it remains only the low frequencies. The signal is still
-            noisy, but it contains mainly low frequencies.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Filtering a signal using the analog filter</title>
-        <para>To filter a signal using an analog filter, we have two
-            strategies:
-        </para>
-        <itemizedlist>
-            <listitem>
-                <para>
-                    transform the analog filter into a discrete one using the <link linkend="dscr">dscr</link> function
-                </para>
-            </listitem>
-            <listitem>
-                <para>
-                    apply the <link linkend="csim">csim</link> function to filter
-                    the signal
-                </para>
-            </listitem>
-        </itemizedlist>
-        <para>
-            First, we try using the <link linkend="dscr">dscr</link> + <link linkend="flts">flts</link> functions.
-        </para>
-        <programlisting role=""><![CDATA[
-rand('normal');
-Input = rand(1,1000); // Produce a random gaussian noise
-n     = 1:1000; // The sample index
-
-eldtf = dscr(elatf,1/100); // Discretization of the linear filter
-y = flts(Input,eldtf); // Filter the signal
-
-subplot(2,1,1);
-plot(n,Input);
-xtitle('The gaussian noise','n','y');
-subplot(2,1,2);
-plot(n,y);
-xtitle('The filtered gaussian noise','n','y');
- ]]></programlisting>
-        <para>Here is the representation of the signal before and after filtering
-            using the <link linkend="dscr">dscr</link> + <link linkend="flts">flts</link> approach.
-        </para>
-        <mediaobject>
-            <imageobject>
-                <imagedata fileref="../../images/analog_filtered_noise.png"/>
-            </imageobject>
-        </mediaobject>
-        <para>
-            Next, we use the <link linkend="csim">csim</link> function.
-        </para>
-        <programlisting role=""><![CDATA[
-rand('normal');
-Input = rand(1,1000); // Produce a random gaussian noise
-t     = 1:1000;
-t     = t*0.01; // Convert sample index into time steps
-
-y = csim(Input,t,elatf); // Filter the signal
-
-subplot(2,1,1);
-plot(t,Input);
-xtitle('The gaussian noise','t','y');
-subplot(2,1,2);
-plot(t,y);
-xtitle('The filtered gaussian noise','t','y');
- ]]></programlisting>
-        <para>Here is the representation of the signal before and after filtering
-            using the <link linkend="csim">csim</link> approach.
-        </para>
-        <mediaobject>
-            <imageobject>
-                <imagedata fileref="../../images/analog_filtered_noise_csim.png"/>
-            </imageobject>
-        </mediaobject>
-        <para>
-            The main difference between the <link linkend="dscr">dscr</link> +
-            <link linkend="flts">flts</link> approach and the <link linkend="csim">csim</link> approach: the <link linkend="dscr">dscr</link>
-            + <link linkend="flts">flts</link> uses samples whereas the <link linkend="csim">csim</link> functions uses time steps.
-        </para>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="bode">bode</link>
-            </member>
-            <member>
-                <link linkend="iir">iir</link>
-            </member>
-            <member>
-                <link linkend="poly">poly</link>
-            </member>
-            <member>
-                <link linkend="syslin">syslin</link>
-            </member>
-            <member>
-                <link linkend="zpell">zpell</link>
-            </member>
-            <member>
-                <link linkend="flts">flts</link>
-            </member>
-            <member>
-                <link linkend="tf2ss">tf2ss</link>
-            </member>
-            <member>
-                <link linkend="dscr">dscr</link>
-            </member>
-            <member>
-                <link linkend="csim">csim</link>
-            </member>
-            <member>
-                <link linkend="trans">trans</link>
-            </member>
-            <member>
-                <link linkend="analpf">analpf</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/identification/frfit.xml b/scilab/modules/signal_processing/help/fr_FR/identification/frfit.xml
deleted file mode 100644 (file)
index 78b869f..0000000
+++ /dev/null
@@ -1,110 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="frfit">
-    <refnamediv>
-        <refname>frfit</refname>
-        <refpurpose>frequency response fit</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>sys=frfit(w,fresp,order)
-            [num,den]=frfit(w,fresp,order)
-            sys=frfit(w,fresp,order,weight)
-            [num,den]=frfit(w,fresp,order,weight)
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>w</term>
-                <listitem>
-                    <para>positive real vector of frequencies (Hz)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>fresp</term>
-                <listitem>
-                    <para>
-                        complex vector of frequency responses (same size as <literal>w</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>order</term>
-                <listitem>
-                    <para>
-                        integer (required order, degree of <literal>den</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>weight</term>
-                <listitem>
-                    <para>
-                        positive real vector (default value <literal>ones(w)</literal>).
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>num,den</term>
-                <listitem>
-                    <para>stable polynomials</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            <literal>sys=frfit(w,fresp,order,weight)</literal> returns a bi-stable transfer function
-            <literal>G(s)=sys=num/den</literal>, of of given <literal>order</literal> such that
-            its frequency response <literal>G(w(i))</literal> matches <literal>fresp(i)</literal>, i.e.
-            <literal>freq(num,den,%i*w)</literal> should be close to <literal>fresp</literal>.
-            <literal>weight(i)</literal> is the weight given to <literal>w(i)</literal>.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-w=0.01:0.01:2;
-s=poly(0,'s');
-G=syslin('c',2*(s.^2+0.1*s+2), (s.^2+s+1)*(s.^2+0.3*s+1));
-fresp=repfreq(G,w);
-Gid=frfit(w,fresp,4);
-frespfit=repfreq(Gid,w);
-bode(w,[fresp;frespfit])
- ]]></programlisting>
-        <scilab:image>
-            w=0.01:0.01:2;
-            s=poly(0,'s');
-            G=syslin('c',2*(s.^2+0.1*s+2), (s.^2+s+1)*(s.^2+0.3*s+1));
-            fresp=repfreq(G,w);
-            Gid=frfit(w,fresp,4);
-            frespfit=repfreq(Gid,w);
-            bode(w,[fresp;frespfit])
-        </scilab:image>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="frep2tf">frep2tf</link>
-            </member>
-            <member>
-                <link linkend="factors">factors</link>
-            </member>
-            <member>
-                <link linkend="cepstrum">cepstrum</link>
-            </member>
-            <member>
-                <link linkend="mrfit">mrfit</link>
-            </member>
-            <member>
-                <link linkend="freq">freq</link>
-            </member>
-            <member>
-                <link linkend="calfrq">calfrq</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/identification/lattn.xml b/scilab/modules/signal_processing/help/fr_FR/identification/lattn.xml
deleted file mode 100644 (file)
index 198a15f..0000000
+++ /dev/null
@@ -1,129 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="lattn">
-    <refnamediv>
-        <refname>lattn</refname>
-        <refpurpose>recursive solution of normal equations</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[la,lb]=lattn(n,p,cov)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>maximum order of the filter</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>p</term>
-                <listitem>
-                    <para>
-                        fixed dimension of the MA part. If <literal>p= -1</literal>, the algorithm reduces to the classical Levinson recursions.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>cov</term>
-                <listitem>
-                    <para>
-                        matrix containing the <literal>Rk</literal>'s (<literal>d*d</literal> matrices for a d-dimensional process).It must be given the following way
-                    </para>
-                    <para>
-                        <latex>
-                            \begin{eqnarray}
-                            \begin{pmatrix}
-                            R_0\\R_1\\R_2\\ \vdots \\R_{nlags}
-                            \end{pmatrix}
-                            \end{eqnarray}
-                        </latex>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>la</term>
-                <listitem>
-                    <para>list-type variable, giving the successively calculated polynomials (degree 1 to degree n),with coefficients Ak</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            solves recursively on <literal>n</literal> (<literal>p</literal> being fixed)
-            the following system (normal equations), i.e. identifies
-            the AR part (poles) of a vector ARMA(n,p) process,
-        </para>
-        <latex>
-            \begin{eqnarray}
-            \begin{pmatrix}
-            I&amp;-A_1&amp;\cdots&amp;-A_n
-            \end{pmatrix}
-            \ast
-            \begin{pmatrix}
-            R_{p+1}&amp;R_{p+2}&amp;\cdots&amp;R_{p+n} \\
-            R_p&amp;R_{p+1}&amp;\cdots&amp;R_{p+n-1} \\
-            R_{p+n-1}&amp;R_p&amp;\cdots&amp;R_{p+n-2} \\
-            \vdots&amp;\vdots&amp;\cdots&amp;\vdots \\
-            R_{p+1-n}&amp;R_{p+2-n}&amp;\cdots&amp;R_p
-            \end{pmatrix}
-            = 0
-            \end{eqnarray}
-        </latex>
-        <para>
-
-        </para>
-
-        <para>
-            where {<literal>Rk;k=1,nlag</literal>} is the sequence of empirical covariances.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Example</title>
-        <programlisting role="Example"><![CDATA[
-//Generate the process
-t1=0:0.1:100;
-y1=sin(2*%pi*t1)+sin(2*%pi*2*t1);
-y1=y1+rand(y1,"normal");
-
-//Covariance of y1
-nlag=128;
-c1=corr(y1,nlag);
-c1=c1';
-
-//Compute the filter with maximum order=15 and p=1
-n=15;
-[la1,sig1]=lattn(n,1,c1);
-
-//Compare result of poles with p=-1 and with levin function
-[la2,sig2]=lattn(n,-1,c1);
-for i=1:n
-  s2=roots(la2(i));
-  s2=log(s2)/2/%pi/.1; //estimated poles
-  s2=gsort(imag(s2));
-  s2=s2(1:i/2);
-end;
-[la3,sig3]=levin(n,c1);
-for i=1:n
-  s3=roots(la3(i));
-  s3=log(s3)/2/%pi/.1; //estimated poles
-  s3=gsort(imag(s3));
-  s3=s3(1:i/2);
-end;
-]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="levin">levin</link>
-            </member>
-            <member>
-                <link linkend="lattp">lattp</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/identification/lattp.xml b/scilab/modules/signal_processing/help/fr_FR/identification/lattp.xml
deleted file mode 100644 (file)
index 8fcb7f0..0000000
+++ /dev/null
@@ -1,88 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="lattp">
-    <refnamediv>
-        <refname>lattp</refname>
-        <refpurpose>Identification of MA part of a vector ARMA process</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[la,lb]=lattp(n,p,cov)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>n</term>
-                <listitem>
-                    <para>maximum order of the filter</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>p</term>
-                <listitem>
-                    <para>
-                        fixed dimension of the MA part. If <literal>p= -1</literal>, the algorithm reduces to the classical Levinson recursions.
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>cov</term>
-                <listitem>
-                    <para>
-                        matrix containing the <literal>Rk</literal>'s (<literal>d*d</literal> matrices for a d-dimensional process).It must be given the following way
-                    </para>
-                    <para>
-                        <latex>
-                            \begin{eqnarray}
-                            \begin{pmatrix}
-                            R_0\\R_1\\R_2\\ \vdots \\R_{nlags}
-                            \end{pmatrix}
-                            \end{eqnarray}
-                        </latex>
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>la</term>
-                <listitem>
-                    <para>list-type variable, giving the successively calculated polynomials (degree 1 to degree p),with coefficients Ak</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            This function identifies the MA part of a vector ARMA(n,p) process.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Example</title>
-        <programlisting role="Example"><![CDATA[
-//Generate the process
-t1=0:0.1:100;
-y1=sin(2*%pi*t1)+sin(2*%pi*2*t1);
-y1=y1+rand(y1,"normal");
-
-//Covariance of y1
-nlag=128;
-c1=corr(y1,nlag);
-c1=c1';
-
-//Compute the filter with maximum order=15 and p=5
-n=5; p=2;
-[la1,sig1]=lattp(n,p,c1);
-]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="levin">levin</link>
-            </member>
-            <member>
-                <link linkend="lattn">lattn</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/identification/mrfit.xml b/scilab/modules/signal_processing/help/fr_FR/identification/mrfit.xml
deleted file mode 100644 (file)
index c3e2249..0000000
+++ /dev/null
@@ -1,107 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="mrfit">
-    <refnamediv>
-        <refname>mrfit</refname>
-        <refpurpose>frequency response fit</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>sys=mrfit(w,mag,order)
-            [num,den]=mrfit(w,mag,order)
-            sys=mrfit(w,mag,order,weight)
-            [num,den]=mrfit(w,mag,order,weight)
-        </synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>w</term>
-                <listitem>
-                    <para>positive real vector of frequencies (Hz)</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>mag</term>
-                <listitem>
-                    <para>
-                        real vector of frequency responses magnitude (same size as <literal>w</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>order</term>
-                <listitem>
-                    <para>
-                        integer (required order, degree of <literal>den</literal>)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>weight</term>
-                <listitem>
-                    <para>
-                        positive real vector (default value <literal>ones(w)</literal>).
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>num,den</term>
-                <listitem>
-                    <para>stable polynomials</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            <literal>sys=mrfit(w,mag,order,weight)</literal> returns a bi-stable transfer function
-            <literal>G(s)=sys=num/den</literal>, of of given <literal>order</literal> such that
-            its frequency response magnitude <literal>abs(G(w(i)))</literal>
-            matches <literal>mag(i)</literal> i.e. <literal>abs(freq(num,den,%i*w))</literal> should be
-            close to <literal>mag</literal>.
-            <literal>weight(i)</literal> is the weight given to <literal>w(i)</literal>.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-w=0.01:0.01:2;
-s=poly(0,'s');
-G=syslin('c',2*(s^2+0.1*s+2),(s^2+s+1)*(s^2+0.3*s+1)); // syslin('c',Num,Den);
-fresp=repfreq(G,w);
-mag=abs(fresp);
-Gid=mrfit(w,mag,4);
-frespfit=repfreq(Gid,w);
-plot2d([w',w'],[mag(:),abs(frespfit(:))])
- ]]></programlisting>
-        <scilab:image>
-            w=0.01:0.01:2;
-            s=poly(0,'s');
-            G=syslin('c',2*(s^2+0.1*s+2),(s^2+s+1)*(s^2+0.3*s+1));
-            fresp=repfreq(G,w);
-            mag=abs(fresp);
-            Gid=mrfit(w,mag,4);
-            frespfit=repfreq(Gid,w);
-            plot2d([w',w'],[mag(:),abs(frespfit(:))])
-        </scilab:image>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="cepstrum">cepstrum</link>
-            </member>
-            <member>
-                <link linkend="frfit">frfit</link>
-            </member>
-            <member>
-                <link linkend="freq">freq</link>
-            </member>
-            <member>
-                <link linkend="calfrq">calfrq</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/identification/phc.xml b/scilab/modules/signal_processing/help/fr_FR/identification/phc.xml
deleted file mode 100644 (file)
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-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="phc">
-    <refnamediv>
-        <refname>phc</refname>
-        <refpurpose>Markovian representation</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[H,F,G]=phc(hk,d,r)</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>hk</term>
-                <listitem>
-                    <para>hankel matrix</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>d</term>
-                <listitem>
-                    <para>dimension of the observation</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>r</term>
-                <listitem>
-                    <para>desired dimension of the state vector for the approximated model</para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>H, F, G</term>
-                <listitem>
-                    <para>relevant matrices of the Markovian model</para>
-                </listitem>
-            </varlistentry>
-        </variablelist>
-    </refsection>
-    <refsection>
-        <title>Description</title>
-        <para>
-            Function which computes the matrices <literal>H, F, G</literal> of a Markovian
-            representation by the principal hankel
-            component approximation method, from the hankel matrix built
-            from the covariance sequence of a stochastic process.
-        </para>
-    </refsection>
-    <refsection>
-        <title>Examples</title>
-        <programlisting role="example"><![CDATA[
-//This example may usefully be compared with the results from
-//the 'levin' macro (see the corresponding help and example)
-//
-//We consider the process defined by two sinusoids (1Hz and 2 Hz)
-//in additive Gaussian noise (this is the observation);
-//the simulated process is sampled at 10 Hz.
-
-t=0:.1:100;rand('normal');
-y=sin(2*%pi*t)+sin(2*%pi*2*t);y=y+rand(y);plot(t,y)
-
-//covariance of y
-
-nlag=128;
-c=corr(y,nlag);
-
-//hankel matrix from the covariance sequence
-//(we can choose to take more information from covariance
-//by taking greater n and m; try it to compare the results !
-
-n=20;m=20;
-h=hank(n,m,c);
-
-//compute the Markov representation (mh,mf,mg)
-//We just take here a state dimension equal to 4 :
-//this is the rather difficult problem of estimating the order !
-//Try varying ns !
-//(the observation dimension is here equal to one)
-
-ns=4;
-[mh,mf,mg]=phc(h,1,ns);
-
-//verify that the spectrum of mf contains the
-//frequency spectrum of the observed process y
-//(remember that y is sampled -in our example
-//at 10Hz (T=0.1s) so that we need
-//to retrieve the original frequencies through the log
-//and correct scaling by the frequency sampling)
-
-s=spec(mf);s=log(s);
-s=s/2/%pi/.1;
-
-//now we get the estimated spectrum
-imag(s),
- ]]></programlisting>
-    </refsection>
-    <refsection role="see also">
-        <title>See also</title>
-        <simplelist type="inline">
-            <member>
-                <link linkend="levin">levin</link>
-            </member>
-        </simplelist>
-    </refsection>
-</refentry>
diff --git a/scilab/modules/signal_processing/help/fr_FR/identification/rpem.xml b/scilab/modules/signal_processing/help/fr_FR/identification/rpem.xml
deleted file mode 100644 (file)
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-<?xml version="1.0" encoding="UTF-8"?>
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" xmlns:scilab="http://www.scilab.org" xml:lang="fr" xml:id="rpem">
-    <refnamediv>
-        <refname>rpem</refname>
-        <refpurpose>Recursive Prediction-Error Minimization estimation</refpurpose>
-    </refnamediv>
-    <refsynopsisdiv>
-        <title>Syntax</title>
-        <synopsis>[w1,[v]]=rpem(w0,u0,y0,[lambda,[k,[c]]])</synopsis>
-    </refsynopsisdiv>
-    <refsection>
-        <title>Arguments</title>
-        <variablelist>
-            <varlistentry>
-                <term>w0</term>
-                <listitem>
-                    <para>
-                        <literal>list(theta,p,l,phi,psi)</literal> where:
-                    </para>
-                    <variablelist>
-                        <varlistentry>
-                            <term>theta</term>
-                            <listitem>
-                                <para>
-                                    [a,b,c] is a real vector of order <literal>3*n</literal>
-                                </para>
-                                <variablelist>
-                                    <varlistentry>
-                                        <term>a,b,c</term>
-                                        <listitem>
-                                            <para>
-                                                <literal>a=[a(1),...,a(n)], b=[b(1),...,b(n)], c=[c(1),...,c(n)]</literal>
-                                            </para>
-                                        </listitem>
-                                    </varlistentry>
-                                </variablelist>
-                            </listitem>
-                        </varlistentry>
-                        <varlistentry>
-                            <term>p</term>
-                            <listitem>
-                                <para>(3*n x 3*n) real matrix.</para>
-                            </listitem>
-                        </varlistentry>
-                        <varlistentry>
-                            <term>phi,psi,l</term>
-                            <listitem>
-                                <para>
-                                    real vector of dimension <literal>3*n</literal>
-                                </para>
-                            </listitem>
-                        </varlistentry>
-                    </variablelist>
-                    <para>
-                        Applicable values for the first call:
-                    </para>
-                    <programlisting role=""><![CDATA[
-theta=phi=psi=l=0*ones(1,3*n). p=eye(3*n,3*n)
- ]]></programlisting>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>u0</term>
-                <listitem>
-                    <para>
-                        real vector of inputs (arbitrary size). (<literal>u0($)</literal> is not used by rpem)
-                    </para>
-                </listitem>
-            </varlistentry>
-            <varlistentry>
-                <term>y0</term>
-                <listitem>
-                    <para>
-                        vector of outputs (same dimension as <literal>u0</literal>). (<literal>y0(1)</literal> is not used by rpem).
-                    </para>
-                    <para>
-                        If the time domain is <literal>(t0,t0+k-1)</literal> the <literal>u0</literal> vector contains the inputs
-                    </para>
-                    <para>
-                        <literal>u(t0),u(t0+1),..,u(t0+k-1)</literal> and <literal>y0</literal> the outputs
-                  &nbs