updated japanese translation: relocating files. 63/8663/2
Rui Hirokawa [Sat, 11 Aug 2012 13:39:13 +0000 (22:39 +0900)]
Change-Id: I8ab82d9b6901959a5169b7909b316444b37c0196

62 files changed:
scilab/modules/linear_algebra/help/ja_JP/addchapter.sce [changed mode: 0755->0644]
scilab/modules/linear_algebra/help/ja_JP/eigen/balanc.xml
scilab/modules/linear_algebra/help/ja_JP/eigen/bdiag.xml
scilab/modules/linear_algebra/help/ja_JP/eigen/gschur.xml
scilab/modules/linear_algebra/help/ja_JP/eigen/gspec.xml
scilab/modules/linear_algebra/help/ja_JP/eigen/hess.xml
scilab/modules/linear_algebra/help/ja_JP/eigen/pbig.xml
scilab/modules/linear_algebra/help/ja_JP/eigen/projspec.xml
scilab/modules/linear_algebra/help/ja_JP/eigen/psmall.xml
scilab/modules/linear_algebra/help/ja_JP/eigen/schur.xml
scilab/modules/linear_algebra/help/ja_JP/eigen/spec.xml
scilab/modules/linear_algebra/help/ja_JP/eigen/sva.xml
scilab/modules/linear_algebra/help/ja_JP/eigen/svd.xml
scilab/modules/linear_algebra/help/ja_JP/factorization/givens.xml
scilab/modules/linear_algebra/help/ja_JP/factorization/householder.xml
scilab/modules/linear_algebra/help/ja_JP/factorization/sqroot.xml
scilab/modules/linear_algebra/help/ja_JP/kernel/colcomp.xml
scilab/modules/linear_algebra/help/ja_JP/kernel/fullrf.xml
scilab/modules/linear_algebra/help/ja_JP/kernel/fullrfk.xml
scilab/modules/linear_algebra/help/ja_JP/kernel/im_inv.xml
scilab/modules/linear_algebra/help/ja_JP/kernel/kernel.xml
scilab/modules/linear_algebra/help/ja_JP/kernel/range.xml
scilab/modules/linear_algebra/help/ja_JP/kernel/rowcomp.xml
scilab/modules/linear_algebra/help/ja_JP/linear/aff2ab.xml
scilab/modules/linear_algebra/help/ja_JP/linear/chol.xml
scilab/modules/linear_algebra/help/ja_JP/linear/inv.xml
scilab/modules/linear_algebra/help/ja_JP/linear/linsolve.xml
scilab/modules/linear_algebra/help/ja_JP/linear/lsq.xml
scilab/modules/linear_algebra/help/ja_JP/linear/lu.xml
scilab/modules/linear_algebra/help/ja_JP/linear/pinv.xml
scilab/modules/linear_algebra/help/ja_JP/linear/qr.xml
scilab/modules/linear_algebra/help/ja_JP/linear/rankqr.xml
scilab/modules/linear_algebra/help/ja_JP/markov/classmarkov.xml
scilab/modules/linear_algebra/help/ja_JP/markov/eigenmarkov.xml
scilab/modules/linear_algebra/help/ja_JP/markov/genmarkov.xml
scilab/modules/linear_algebra/help/ja_JP/matrix/cond.xml
scilab/modules/linear_algebra/help/ja_JP/matrix/det.xml
scilab/modules/linear_algebra/help/ja_JP/matrix/orth.xml
scilab/modules/linear_algebra/help/ja_JP/matrix/rank.xml
scilab/modules/linear_algebra/help/ja_JP/matrix/rcond.xml
scilab/modules/linear_algebra/help/ja_JP/matrix/rref.xml
scilab/modules/linear_algebra/help/ja_JP/matrix/trace.xml
scilab/modules/linear_algebra/help/ja_JP/matrix_log/expm.xml
scilab/modules/linear_algebra/help/ja_JP/matrix_log/polar.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/companion.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/ereduc.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/fstair.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/glever.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/kroneck.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/lyap.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/pencan.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/penlaur.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/quaskro.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/randpencil.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/rowshuff.xml
scilab/modules/linear_algebra/help/ja_JP/pencil/sylv.xml
scilab/modules/linear_algebra/help/ja_JP/proj.xml
scilab/modules/linear_algebra/help/ja_JP/state_space/coff.xml
scilab/modules/linear_algebra/help/ja_JP/state_space/nlev.xml
scilab/modules/linear_algebra/help/ja_JP/subspaces/spaninter.xml
scilab/modules/linear_algebra/help/ja_JP/subspaces/spanplus.xml
scilab/modules/linear_algebra/help/ja_JP/subspaces/spantwo.xml

old mode 100755 (executable)
new mode 100644 (file)
index 0d3ebf0..cdc451a
@@ -7,5 +7,5 @@
 // are also available at
 // http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
 
-add_help_chapter("Linear Algebra",SCI+"/modules/linear_algebra/help/en_US",%T);
+add_help_chapter("Linear Algebra",SCI+"/modules/linear_algebra/help/ja_JP",%T);
 
index bcc2b93..500672d 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="balanc">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="balanc">
     <refnamediv>
         <refname>balanc</refname>
-        <refpurpose> matrix or pencil balancing</refpurpose>
+        <refpurpose>行列またはペンシルの平衡化</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[Ab,X]=balanc(A)
             [Eb,Ab,X,Y]=balanc(E,A)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>引数</title>
         <variablelist>
             <varlistentry>
                 <term>A:  </term>
                 <listitem>
-                    <para>a real square matrix</para>
+                    <para>実数正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>X:  </term>
                 <listitem>
-                    <para>a real square invertible matrix</para>
+                    <para>可逆な実数正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>E:  </term>
                 <listitem>
                     <para>
-                        a real square matrix (same dimension as <literal>A</literal>)
+                        実数正方行列 (<literal>A</literal>と同じ次元)
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Y:  </term>
                 <listitem>
-                    <para>a real square invertible matrix.</para>
+                    <para>可逆な実数正方行列.</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Balance a square matrix to improve
-            its condition number.
+            正方行列の条件数を改善するために平衡化します.
         </para>
         <para>
-            <literal>[Ab,X] = balanc(A)</literal> finds a similarity transformation
-            <literal>X</literal> such that
+            <literal>[Ab,X] = balanc(A)</literal> は,
+            <literal>Ab = inv(X)*A*X</literal>が近似的に等しい
+            行ノルムおよび列ノルムを有する
+            相似変換<literal>X</literal>を見つけます.
         </para>
         <para>
-            <literal>Ab = inv(X)*A*X</literal> has approximately equal row and column norms.
+            行列ペンシルの場合,平衡化は一般化固有値問題を改善することにより
+            行われます.
         </para>
         <para>
-            For matrix pencils,balancing is done for improving the
-            generalized eigenvalue problem.
-        </para>
-        <para>
-            <literal>[Eb,Ab,X,Y] = balanc(E,A)</literal> returns left and right transformations <literal>X</literal> and <literal>Y</literal>
-            such that <literal>Eb=inv(X)*E*Y,  Ab=inv(X)*A*Y</literal>
+            <literal>[Eb,Ab,X,Y] = balanc(E,A)</literal> は,
+            <literal>Eb=inv(X)*E*Y,  Ab=inv(X)*A*Y</literal> となるような
+            左および右変換
+            <literal>X</literal> および <literal>Y</literal> を返します.
         </para>
     </refsection>
     <refsection>
-        <title>Remark</title>
+        <title>注意</title>
         <para>
-            Balancing is made in the functions <literal>bdiag</literal> and <literal>spec</literal>.
+            平衡化は関数<literal>bdiag</literal> および <literal>spec</literal>
+            で行われます.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=[1/2^10,1/2^10;2^10,2^10];
 [Ab,X]=balanc(A);
@@ -89,8 +90,8 @@ norm(A(1,:))/norm(A(2,:))
 norm(Ab(1,:))/norm(Ab(2,:))
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="bdiag">bdiag</link>
index 29102fe..2b9a69b 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="bdiag">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="bdiag">
     <refnamediv>
         <refname>bdiag</refname>
-        <refpurpose> block diagonalization, generalized eigenvectors</refpurpose>
+        <refpurpose>ブロック対角化, 一般化固有ベクトル</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[Ab [,X [,bs]]]=bdiag(A [,rmax])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>引数</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex square matrix</para>
+                    <para>実数または複素数の正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>rmax</term>
                 <listitem>
-                    <para>real number</para>
+                    <para>実数</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Ab</term>
                 <listitem>
-                    <para>real or complex square matrix</para>
+                    <para>実数または複素数の正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>real or complex non-singular matrix</para>
+                    <para>実数または複素数の正則行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>bs</term>
                 <listitem>
-                    <para>vector of integers</para>
+                    <para>整数ベクトル</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
-        <programlisting role=""><![CDATA[ 
+        <title>説明</title>
+        <programlisting role = ""><![CDATA[ 
 [Ab [,X [,bs]]]=bdiag(A [,rmax]) 
  ]]></programlisting>
         <para>
-            performs the block-diagonalization of matrix <literal>A</literal>.  bs
-            gives the structure of the blocks (respective sizes of the
-            blocks).  <literal>X</literal> is the change of basis i.e 
-            <literal>Ab = inv(X)*A*X</literal>is block diagonal.
+            は,行列<literal>A</literal>のブロック対角化を行ないます.
+            bs はブロックの構造(個々のブロックの大きさ)を出力します.
+            <literal>X</literal> は基底変換です.
+            すなわち, <literal>Ab = inv(X)*A*X</literal> はブロック対角です.
         </para>
         <para>
-            <literal>rmax</literal> controls the conditioning of <literal>X</literal>; the
-            default value is the l1 norm of <literal>A</literal>.
+            <literal>rmax</literal> は<literal>X</literal>の
+            条件数を制御します;
+            デフォルト値は <literal>A</literal> の l1ノルムです.
         </para>
         <para>
-            To get a diagonal form (if it exists) choose a large value for
-            <literal>rmax</literal> (<literal>rmax=1/%eps</literal> for example).
-            Generically (for real random A) the blocks are (1x1) and (2x2) and
-            <literal>X</literal> is the matrix of eigenvectors.
+            (存在する場合,)対角形式を得るには<literal>rmax</literal>に
+            大きな値を指定します(例えば,<literal>rmax=1/%eps</literal>).
+            一般に(ランダムな実数の Aの場合) ブロックは (1x1) および (2x2) で,
+            <literal>X</literal> は固有値の行列です.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
-//Real case: 1x1 and 2x2 blocks
+//実数の場合: 1x1 および 2x2 ブロック
 a=rand(5,5);[ab,x,bs]=bdiag(a);ab
 
-//Complex case: complex 1x1 blocks
+//複素数の場合: 複素数 1x1 ブロック
 [ab,x,bs]=bdiag(a+%i*0);ab
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="schur">schur</link>
index b218164..30438dc 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="gschur">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="gschur">
     <refnamediv>
         <refname>gschur</refname>
-        <refpurpose>
-            generalized Schur form. <emphasis role="bold">This function is obsolete.</emphasis>
-        </refpurpose>
+        <refpurpose>一般化Schur分解 (古い関数).  </refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[As,Es]=gschur(A,E)
             [As,Es,Q,Z]=gschur(A,E)
             [As,Es,Z,dim] = gschur(A,E,flag)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            This function is obsolete and is now included in the <literal>schur</literal>
-            function. In most cases the <literal>gschur</literal> function will still work as
-            before, but it will be removed in the future release. 
+            この関数は古い関数であり,  <literal>schur</literal>関数に統合されています.
+            多くの場合, <literal>gschur</literal>関数は以前と同様に動作しますが,
+            将来のリリースでは削除される予定です.
         </para>
         <para>
-            The first three syntaxes can be replaced by
+            最初の3つの構文は以下のように置き換えることができます
         </para>
-        <programlisting role=""><![CDATA[ 
+        <programlisting role = ""><![CDATA[ 
 [As,Es]=schur(A,E)
 [As,Es,Q,Z]=schur(A,E);Q=Q' //NOTE THE TRANPOSITION HERE
 [As,Es,Z,dim] = schur(A,E,flag) 
  ]]></programlisting>
         <para>
-            The last syntax requires little more adaptations:
+            最後の構文はさらに若干の調整が必要です:
         </para>
         <variablelist>
             <varlistentry>
-                <term>if</term>
+                <term>もし,</term>
                 <listitem>
-                    <para>extern is a scilab function  the new calling sequence
-                        should be <literal>[As,Es,Z,dim]= schur(A,E,Nextern)</literal> with
-                        Nextern defined as follow:
+                    <para>extern が Scilab関数の場合,
+                        新しい呼び出し手順は, Nextern を以下のように定義するとき,
+                        <literal>[As,Es,Z,dim]= schur(A,E,Nextern)</literal>
+                        となります:
                     </para>
-                    <programlisting role=""><![CDATA[ 
+                    <programlisting role = ""><![CDATA[ 
 function t=Nextern(R)
 if R(2)==0 then
   t=extern([1,R(1),R(3)])==1
@@ -66,13 +65,16 @@ endfunction
             <varlistentry>
                 <term>if</term>
                 <listitem>
-                    <para>extern is the name of an external function coded in Fortran or C
-                        the new calling sequence should be <literal>[As,Es,Z,dim]=    schur(A,E,'nextern')</literal> with nextern defined as follow:
+                    <para>extern は,Fortran または Cで記述された外部関数の名前です.
+                        新しい呼び出し手順は,
+                        nextern を以下のように定義すると
+                        <literal>[As,Es,Z,dim]=    schur(A,E,'nextern')</literal> 
+                        のようになります:
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
-        <programlisting role=""><![CDATA[ 
+        <programlisting role = ""><![CDATA[ 
 logical function nextern(ar,ai,beta)
 double precision ar,ai,beta
 integer r,extern
@@ -85,8 +87,8 @@ nextern=r.eq.1
 end
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="external">external</link>
index dbde0cb..f6a0ffc 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="gspec">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="gspec">
     <refnamediv>
         <refname>gspec</refname>
-        <refpurpose>
-            eigenvalues of matrix pencil. <emphasis role="bold">This function is obsolete.</emphasis>
-        </refpurpose>
+        <refpurpose>行列ペンシルの固有値 (古い関数)  </refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[al,be]=gspec(A,E)
             [al,be,Z]=gspec(A,E)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            This function is now included in the <literal>spec</literal> function.
-            the calling syntax must be replaced by
+            この関数は現在では <literal>spec</literal> 関数に統合されています.
+            呼び出し手順は以下のように置き換られています
         </para>
-        <programlisting role=""><![CDATA[ 
+        <programlisting role = ""><![CDATA[ 
 [al,be]=spec(A,E)
 [al,be,Z]=spec(A,E)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="spec">spec</link>
index f9cc5c5..468079d 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="hess">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="hess">
     <refnamediv>
         <refname>hess</refname>
-        <refpurpose> Hessenberg form</refpurpose>
+        <refpurpose>ヘッセンベルク形式</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>H = hess(A)
             [U,H] = hess(A)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex square matrix</para>
+                    <para>実数または複素数の正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>H</term>
                 <listitem>
-                    <para>real or complex square matrix</para>
+                    <para>実数または複素数の正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>U</term>
                 <listitem>
-                    <para>orthogonal or unitary square matrix</para>
+                    <para>直交またはユニタリ正方行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>[U,H] = hess(A)</literal> produces a unitary matrix
-            <literal>U</literal> and a Hessenberg matrix <literal>H</literal> so that
-            <literal>A = U*H*U'</literal> and <literal>U'*U</literal> =
-            Identity.  By itself, <literal>hess(A)</literal> returns <literal>H</literal>.
+            <literal>[U,H] = hess(A)</literal> は,
+            <literal>A = U*H*U'</literal> および <literal>U'*U</literal> =単位行列 となるような
+            ユニタリ行列<literal>U</literal> およびヘッセンベルク行列<literal>H</literal>を出力します.
+            これにより, <literal>hess(A)</literal> は <literal>H</literal>を返します.
         </para>
-        <para>
-            The Hessenberg form of a matrix is zero below the first
-            subdiagonal. If the matrix is symmetric or Hermitian, the form is
-            tridiagonal.
+        <para>行列のヘッセンベルク形式は最初の副対角線以下では 0となります.
+            この行列が対称またはエルミート行列の場合,
+            形は3重対角となります.
         </para>
     </refsection>
     <refsection>
-        <title>References</title>
+        <title>リファレンス</title>
         <para>
-            hess function is based on the Lapack routines
-            DGEHRD, DORGHR for  real matrices and  ZGEHRD, ZORGHR for the complex case.
+            hess 関数は Lapack ルーチン
+            DGEHRD, DORGHR (実数行列の場合) および ZGEHRD, ZORGHR (複素数行列の場合)に基づいています.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(3,3);[U,H]=hess(A);
 and( abs(U*H*U'-A)<1.d-10 )
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="qr">qr</link>
@@ -87,11 +86,11 @@ and( abs(U*H*U'-A)<1.d-10 )
         </simplelist>
     </refsection>
     <refsection>
-        <title>Used Functions</title>
+        <title>使用される関数</title>
         <para>
-            <literal>hess</literal> function is based on the Lapack routines
-            DGEHRD, DORGHR for  real matrices and  ZGEHRD, ZORGHR for the
-            complex  case.
+            <literal>hess</literal> 関数はLapack ルーチン
+            DGEHRD, DORGHR (実数行列の場合) および  ZGEHRD, ZORGHR (複素数行列の場合)に
+            基づいています.
         </para>
     </refsection>
 </refentry>
index 9291150..010d966 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="pbig">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="pbig">
     <refnamediv>
         <refname>pbig</refname>
-        <refpurpose> eigen-projection</refpurpose>
+        <refpurpose>固有投影</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[Q,M]=pbig(A,thres,flag)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>Parameters</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real square matrix</para>
+                    <para>実数正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>thres</term>
                 <listitem>
-                    <para>real number</para>
+                    <para>実数</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>flag</term>
                 <listitem>
                     <para>
-                        character string (<literal>'c'</literal> or <literal>'d'</literal>)
+                        文字列 (<literal>'c'</literal> または <literal>'d'</literal>)
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Q,M</term>
                 <listitem>
-                    <para>real matrices</para>
+                    <para>実数行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Projection on eigen-subspace associated with eigenvalues with real
-            part &gt;= <literal>thres</literal> (<literal>flag='c'</literal>) or
-            with magnitude &gt;= <literal>thres</literal>
-            (<literal>flag='d'</literal>).
+            実部&gt;= <literal>thres</literal> (<literal>flag='c'</literal>)
+            または
+            大きさ&gt;= <literal>thres</literal>(<literal>flag='d'</literal>)
+            の固有値を有する固有値-部分空間への投影.
         </para>
         <para>
-            The projection is defined by <literal>Q*M</literal>, <literal>Q</literal> is
-            full column rank, <literal>M</literal> is full row rank and
+            投影は<literal>Q*M</literal>により定義され,<literal>Q</literal>
+            は列フルランク, <literal>M</literal>は行フルランクおよび
             <literal>M*Q=eye</literal>.
         </para>
         <para>
-            If <literal>flag='c'</literal>, the eigenvalues of
-            <literal>M*A*Q</literal> = eigenvalues of <literal>A</literal> with real part
-            &gt;= <literal>thres</literal>.
+            <literal>flag='c'</literal>の場合, 
+            <literal>M*A*Q</literal>の固有値 = 実部&gt;= <literal>thres</literal>
+            の<literal>A</literal>の固有値となります.
         </para>
         <para>
-            If <literal>flag='d'</literal>, the eigenvalues of
-            <literal>M*A*Q</literal> = eigenvalues of <literal>A</literal> with magnitude
-            &gt;= <literal>thres</literal>.
+            <literal>flag='d'</literal>の場合, 
+            <literal>M*A*Q</literal>の固有値 = 大きさ&gt;= <literal>thres</literal>の
+            <literal>A</literal>の固有値となります.
         </para>
         <para>
-            If <literal>flag='c'</literal> and if <literal>[Q1,M1]</literal> =
-            full rank factorization (<literal>fullrf</literal>) of
-            <literal>eye()-Q*M</literal> then eigenvalues of <literal>M1*A*Q1</literal> =
-            eigenvalues of <literal>A</literal> with real part &lt;
-            <literal>thres</literal>.
+            <literal>flag='c'</literal> の場合,そして
+            <literal>[Q1,M1]</literal> = <literal>eye()-Q*M</literal>の
+            フルランク分解 (<literal>fullrf</literal>)の場合,
+            <literal>M1*A*Q1</literal>の固有値 =
+            実部 &lt; <literal>thres</literal>の<literal>A</literal>の固有値となります.
         </para>
         <para>
-            If <literal>flag='d'</literal> and if <literal>[Q1,M1]</literal> =
-            full rank factorization (<literal>fullrf</literal>) of
-            <literal>eye()-Q*M</literal> then eigenvalues of <literal>M1*A*Q1</literal> =
-            eigenvalues of <literal>A</literal> with magnitude &lt;
-            <literal>thres</literal>.
+            <literal>flag='d'</literal>の場合,そして <literal>[Q1,M1]</literal> =
+            <literal>eye()-Q*M</literal>のフルランク分解 (<literal>fullrf</literal>)の場合,
+            <literal>M1*A*Q1</literal>の固有値 =大きさ &lt;<literal>thres</literal>の
+            <literal>A</literal>の固有値となります.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=diag([1,2,3]);X=rand(A);A=inv(X)*A*X;
 [Q,M]=pbig(A,1.5,'d');
@@ -98,8 +97,8 @@ spec(M*A*Q)
 spec(M1*A*Q1)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="psmall">psmall</link>
@@ -116,10 +115,15 @@ spec(M1*A*Q1)
         </simplelist>
     </refsection>
     <refsection>
-        <title>Used Functions</title>
+        <title>作者</title>
+        <para>F. D. (1988); ;   </para>
+    </refsection>
+    <refsection>
+        <title>使用される関数</title>
         <para>
-            <literal>pbig</literal> is based on the ordered schur form (scilab
-            function <literal>schur</literal>).
+            <literal>pbig</literal> は
+            ソートされた Schur 形式に基づいています
+            (Scilab関数 <literal>schur</literal>).
         </para>
     </refsection>
 </refentry>
index 9612a11..41e66d9 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="projspec">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="projspec">
     <refnamediv>
         <refname>projspec</refname>
-        <refpurpose> spectral operators</refpurpose>
+        <refpurpose>スペクトル演算子</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[S,P,D,i]=projspec(A)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>square matrix</para>
+                    <para>正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>S, P, D</term>
                 <listitem>
-                    <para>square matrices</para>
+                    <para>s正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>i</term>
                 <listitem>
                     <para>
-                        integer (index of the zero eigenvalue of <literal>A</literal>).
+                        整数 (<literal>A</literal>のゼロ固有値の添字).
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Spectral characteristics of <literal>A</literal> at 0.
+            <literal>A</literal>の0におけるスペクトル特性.
         </para>
         <para>
-            <literal>S</literal> = reduced resolvent at 0 (<literal>S</literal> = -Drazin_inverse(<literal>A</literal>)).
+            <literal>S</literal> = 0における縮小レゾルベント 
+            (<literal>S</literal> = -Drazin_inverse(<literal>A</literal>)).
         </para>
         <para>
-            <literal>P</literal> = spectral projection at 0.
+            <literal>P</literal> = 0におけるスペクトル投影.
         </para>
         <para>
-            <literal>D</literal> = nilpotent operator at 0.
+            <literal>D</literal> = 0における冪零演算子.
         </para>
         <para>
-            <literal>index</literal> = index of the 0 eigenvalue.
+            <literal>index</literal> = 0固有値の添字.
         </para>
         <para>
-            One has <literal>(s*eye()-A)^(-1) = D^(i-1)/s^i +... + D/s^2 + P/s - S - s*S^2 -...</literal>
-            around the singularity s=0.
+            特異点s=0の周りでの
+            <literal>(s*eye()-A)^(-1) = D^(i-1)/s^i +... + D/s^2 + P/s - S - s*S^2 -...</literal>
+            が出力されます.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 deff('j=jdrn(n)','j=zeros(n,n);for k=1:n-1;j(k,k+1)=1;end')
 A=sysdiag(jdrn(3),jdrn(2),rand(2,2));X=rand(7,7);
 A=X*A*inv(X);
 [S,P,D,index]=projspec(A);
-index   //size of J-block
-trace(P)  //sum of dimensions of J-blocks
+index   //J-ブロックの大きさ
+trace(P)  //J-ブロックの次元の合計
 A*S-(eye()-P)
 norm(D^index,1)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="coff">coff</link>
             </member>
         </simplelist>
     </refsection>
+    <refsection>
+        <title>作者</title>
+        <para>F. D.; ;   </para>
+    </refsection>
 </refentry>
index a4a27f3..3414a2d 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="psmall">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="psmall">
     <refnamediv>
         <refname>psmall</refname>
-        <refpurpose> spectral projection</refpurpose>
+        <refpurpose>スペクトル投影</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[Q,M]=psmall(A,thres,flag)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real square matrix</para>
+                    <para>実数の正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>thres</term>
                 <listitem>
-                    <para>real number</para>
+                    <para>実数</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>flag</term>
                 <listitem>
                     <para>
-                        character string (<literal>'c'</literal> or <literal>'d'</literal>)
+                        文字列 (<literal>'c'</literal> または <literal>'d'</literal>)
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Q,M</term>
                 <listitem>
-                    <para>real matrices</para>
+                    <para>実数行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Projection on eigen-subspace associated with eigenvalues with real
-            part &lt; <literal>thres</literal> (<literal>flag='c'</literal>) or
-            with modulus &lt; <literal>thres</literal>
-            (<literal>flag='d'</literal>).
+            実部 &lt; <literal>thres</literal> (<literal>flag='c'</literal>)
+            または絶対値 &lt; <literal>thres</literal>(<literal>flag='d'</literal>)
+            となる固有値-部分空間への投影.
         </para>
         <para>
-            The projection is defined by <literal>Q*M</literal>, <literal>Q</literal> is
-            full column rank, <literal>M</literal> is full row rank and
-            <literal>M*Q=eye</literal>.
+            この投影は<literal>Q*M</literal>により定義されます.
+            ここで,
+            <literal>Q</literal>は列フルランク,<literal>M</literal>は行フルランク,
+            そして<literal>M*Q=eye</literal>です.
         </para>
         <para>
-            If <literal>flag='c'</literal>, the eigenvalues of
-            <literal>M*A*Q</literal> = eigenvalues of <literal>A</literal> with real part
-            &lt; <literal>thres</literal>.
+            <literal>flag='c'</literal>の場合, 
+            <literal>M*A*Q</literal>の固有値 = 
+            実部&lt; <literal>thres</literal>の<literal>A</literal>の固有値.
         </para>
         <para>
-            If <literal>flag='d'</literal>, the eigenvalues of
-            <literal>M*A*Q</literal> = eigenvalues of <literal>A</literal> with magnitude
-            &lt; <literal>thres</literal>.
+            <literal>flag='d'</literal>の場合, 
+            <literal>M*A*Q</literal>の固有値 = 
+            大きさ &lt; <literal>thres</literal>の<literal>A</literal>の固有値.
         </para>
         <para>
-            If <literal>flag='c'</literal> and if <literal>[Q1,M1]</literal> =
-            full rank factorization (<literal>fullrf</literal>) of
-            <literal>eye()-Q*M</literal> then eigenvalues of <literal>M1*A*Q1</literal> =
-            eigenvalues of <literal>A</literal> with real part &gt;=
-            <literal>thres</literal>.
+            <literal>flag='c'</literal>の場合, 
+            <literal>[Q1,M1]</literal> = <literal>eye()-Q*M</literal>の
+            フルランク分解(<literal>fullrf</literal>)の場合,
+            <literal>M1*A*Q1</literal>の固有値 =実部&gt;=
+            <literal>thres</literal>の
+            <literal>A</literal>の固有値となります.
         </para>
         <para>
-            If <literal>flag='d'</literal> and if <literal>[Q1,M1]</literal> =
-            full rank factorization (<literal>fullrf</literal>) of
-            <literal>eye()-Q*M</literal> then eigenvalues of <literal>M1*A*Q1</literal> =
-            eigenvalues of <literal>A</literal> with magnitude &gt;=
-            <literal>thres</literal>.
+            <literal>flag='d'</literal>の場合,
+            <literal>[Q1,M1]</literal> =<literal>eye()-Q*M</literal>
+            のフルランク分解(<literal>fullrf</literal>)の場合,
+            <literal>M1*A*Q1</literal>の固有値 =
+            大きさ&gt;=<literal>thres</literal>の
+            <literal>A</literal>の固有値.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=diag([1,2,3]);X=rand(A);A=inv(X)*A*X;
 [Q,M]=psmall(A,2.5,'d');
@@ -98,8 +100,8 @@ spec(M*A*Q)
 spec(M1*A*Q1)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="pbig">pbig</link>
@@ -113,10 +115,14 @@ spec(M1*A*Q1)
         </simplelist>
     </refsection>
     <refsection>
-        <title>Used Functions</title>
+        <title>作者</title>
+        <para>F. Delebecque INRIA. (1988);   </para>
+    </refsection>
+    <refsection>
+        <title>使用される関数</title>
         <para>
-            This function is  based on the ordered schur form (scilab
-            function <literal>schur</literal>).
+            この関数はソートされた Schur形式(scilab
+            関数 <literal>schur</literal>)に基づいています.
         </para>
     </refsection>
 </refentry>
index c8043ea..88e79d4 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="schur">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="schur">
     <refnamediv>
         <refname>schur</refname>
-        <refpurpose> [ordered] Schur decomposition of matrix and pencils</refpurpose>
+        <refpurpose> 行列およびペンシルの[ソートされた] Schur 分解</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[U,T] = schur(A)
             [U,dim [,T] ]=schur(A,flag)
             [U,dim [,T] ]=schur(A,extern1)
             
             [As,Es [,Q,Z]]=schur(A,E)
-            [As,Es [,Z,dim]] = schur(A,E,flag)
+            [As,Es [,Q],Z,dim] = schur(A,E,flag)
             [Z,dim] = schur(A,E,flag)
-            [As,Es [,Z,dim]]= schur(A,E,extern2)
+            [As,Es [,Q],Z,dim]= schur(A,E,extern2)
             [Z,dim]= schur(A,E,extern2)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>引数</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex square matrix.</para>
+                    <para>実数または複素数の正方行列.</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>E</term>
                 <listitem>
                     <para>
-                        real or complex square matrix with same dimensions as <literal> A</literal>.
+                        <literal>A</literal>と同じ次元の実数または複素数の正方行列.
                     </para>
                 </listitem>
             </varlistentry>
                 <term>flag</term>
                 <listitem>
                     <para>
-                        character string (<literal>'c'</literal> or <literal>'d'</literal>)
+                        文字列 (<literal>'c'</literal> または <literal>'d'</literal>)
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>extern1</term>
                 <listitem>
-                    <para>an ``external'', see below</para>
+                    <para>an ``external'', 以下の参照</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>extern2</term>
                 <listitem>
-                    <para>an ``external'', see below</para>
+                    <para>an ``external'', 以下の参照</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>U</term>
                 <listitem>
-                    <para>orthogonal or unitary square matrix</para>
+                    <para>直交またはユニタリ正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Q</term>
                 <listitem>
-                    <para>orthogonal or unitary square matrix</para>
+                    <para>直交またはユニタリ正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Z</term>
                 <listitem>
-                    <para>orthogonal or unitary square matrix</para>
+                    <para>o直交またはユニタリ正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>T</term>
                 <listitem>
-                    <para>upper triangular or quasi-triangular square matrix</para>
+                    <para>上三角または準三角正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>As</term>
                 <listitem>
-                    <para>upper triangular or quasi-triangular square matrix</para>
+                    <para>上三角または準三角正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Es</term>
                 <listitem>
-                    <para>upper triangular  square matrix</para>
+                    <para>上三角正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>dim</term>
                 <listitem>
-                    <para>integer</para>
+                    <para>整数</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Schur forms, ordered Schur forms of matrices and pencils
+            Schur 形式, 行列およびペンシルのソートされた Schur 形式
         </para>
         <variablelist>
             <varlistentry>
-                <term>MATRIX SCHUR FORM</term>
+                <term>行列Schur形式</term>
                 <listitem>
                     <variablelist>
                         <varlistentry>
-                            <term>Usual schur form:</term>
+                            <term>通常のSchur形式:</term>
                             <listitem>
                                 <para>
-                                    <literal>[U,T] = schur(A)</literal> produces a Schur matrix
-                                    <literal>T</literal> and a unitary matrix <literal>U</literal> so that
-                                    <literal>A = U*T*U'</literal> and <literal>U'*U =  eye(U)</literal>. By itself, schur(<literal>A</literal>) returns
-                                    <literal>T</literal>. If <literal>A</literal> is complex, the Complex
-                                    Schur Form is returned in matrix
-                                    <literal>T</literal>. The Complex Schur Form is upper triangular with
-                                    the eigenvalues of <literal>A</literal> on the diagonal. If
-                                    <literal>A</literal> is real, the Real Schur Form is returned.  The Real
-                                    Schur Form has the real eigenvalues on the diagonal and the
-                                    complex eigenvalues in 2-by-2 blocks on the diagonal.
+                                    <literal>[U,T] = schur(A)</literal> は,
+                                    <literal>A = U*T*U'</literal> および <literal>U'*U =  eye(U)</literal>となるような
+                                    Schur行列<literal>T</literal> およびユニタリ行列 <literal>U</literal>
+                                    を出力します.
+                                    Schur(<literal>A</literal>)は,<literal>T</literal>を返します.
+                                    <literal>A</literal> が複素数の場合, 複素Schur形式は,行列<literal>T</literal>に返します.
+                                    複素Schur形式は,<literal>A</literal>の固有値を対角項に有する上三角行列です.
+                                    <literal>A</literal> が実数の場合, 実数Schur形式が返されます.
+                                    実数Schur形式は,対角項に実数固有値、複素数固有値を対角項の2x2ブロックに
+                                    有します.
                                 </para>
                             </listitem>
                         </varlistentry>
                         <varlistentry>
-                            <term>Ordered Schur forms</term>
+                            <term>ソートされたSchur形式</term>
                             <listitem>
                                 <para>
-                                    <literal>[U,dim]=schur(A,'c')</literal> returns an unitary
-                                    matrix <literal>U</literal> which transforms <literal>A</literal> into schur
-                                    form.  In addition, the dim first columns of <literal>U</literal> make
-                                    a basis of the eigenspace of <literal>A</literal> associated with
-                                    eigenvalues with negative real parts (stable "continuous
-                                    time" eigenspace).
+                                    <literal>[U,dim]=schur(A,'c')</literal> は,
+                                    <literal>A</literal>を Schur 形式に変換する
+                                    ユニタリ行列 <literal>U</literal> を返します.
+                                    更に,<literal>U</literal>の最初の列 dim は,
+                                    実部が負の固有値(安定な"連続時間"固有値空間)
+                                    に関連する<literal>A</literal>の固有値空間
+                                    の基底を構成します.
                                 </para>
+                                
                                 <para>
-                                    <literal>[U,dim]=schur(A,'d')</literal> returns an unitary
-                                    matrix <literal>U</literal> which transforms <literal>A</literal> into schur
-                                    form.  In addition, the <literal>dim</literal> first columns of
-                                    <literal>U</literal> span a basis of the eigenspace of <literal>A</literal>
-                                    associated with eigenvalues with magnitude lower than 1 (stable
-                                    "discrete time" eigenspace).
+                                    <literal>[U,dim]=schur(A,'d')</literal> は,
+                                    <literal>A</literal>を Schur 形式に変換する
+                                    ユニタリ行列 <literal>U</literal> を返します.
+                                    更に,<literal>U</literal>の最初の列 dim は,
+                                    大きさが1未満の固有値(安定な"離散時間"固有値空間)
+                                    に関連する<literal>A</literal>の固有値空間
+                                    の基底を構成します.
                                 </para>
                                 <para>
-                                    <literal>[U,dim]=schur(A,extern1)</literal> returns an unitary matrix
-                                    <literal>U</literal> which transforms <literal>A</literal> into schur form.
-                                    In addition, the <literal>dim</literal> first columns of
-                                    <literal>U</literal> span a basis of the eigenspace of <literal>A</literal>
-                                    associated with the eigenvalues which are selected by the
-                                    external function <literal>extern1</literal> (see external for
-                                    details).  This external can be described by a Scilab function
-                                    or by C or Fortran procedure: 
+                                    <literal>[U,dim]=schur(A,extern1)</literal> は,
+                                    <literal>A</literal>を Schur 形式に変換する
+                                    ユニタリ行列<literal>U</literal>を返します.
+                                    更に,<literal>U</literal>の最初の列 dim は,
+                                    外部関数 <literal>extern1</literal> (詳細は external 参照)
+                                    により選択された固有値に関連する<literal>A</literal>の固有値空間
+                                    の基底を構成します.
+                                    この external はScilab関数またはCまたはFortranプロシージャにより
+                                    次のように記述することができます: 
                                 </para>
                                 <variablelist>
                                     <varlistentry>
-                                        <term>a Scilab function</term>
+                                        <term>Scilab関数</term>
                                         <listitem>
                                             <para>
-                                                If <literal>extern1</literal> is described by a Scilab function, it
-                                                should have the following calling sequence:
-                                                <literal>s=extern1(Ev)</literal>, where <literal>Ev</literal> is an eigenvalue and
-                                                <literal>s</literal> a boolean.
+                                                <literal>extern1</literal>が
+                                                Scilab関数により記述される場合,
+                                                以下の呼び出し手順を有する必要があります:
+                                                <literal>s=extern1(Ev)</literal>, ただし <literal>Ev</literal> は固有値,
+                                                <literal>s</literal> は論理値です.
                                             </para>
                                         </listitem>
                                     </varlistentry>
                                     <varlistentry>
-                                        <term>a C or Fortran procedure</term>
+                                        <term>C または Fortran プロシージャ</term>
                                         <listitem>
                                             <para>
-                                                If <literal>extern1</literal> is described by a C or Fortran function it
-                                                should have the following calling sequence:
+                                                <literal>extern1</literal> がCまたはFortran関数により
+                                                記述される場合,以下の呼び出し手順を有する必要があります:
                                                 <literal>int extern1(double *EvR, double *EvI)</literal>
-                                                where <literal>EvR</literal> and <literal>EvI</literal> are  eigenvalue real and complex parts.
-                                                a true or non zero returned value stands for selected eigenvalue.
+                                                ただし <literal>EvR</literal> および <literal>EvI</literal> は
+                                                固有値の実部および虚部です.
+                                                trueまたはゼロでない戻り値は,選択された固有値を意味します.
                                             </para>
                                         </listitem>
                                     </varlistentry>
                 </listitem>
             </varlistentry>
             <varlistentry>
-                <term>PENCIL SCHUR FORMS</term>
+                <term>ペンシルSchur形式</term>
                 <listitem>
                     <variablelist>
                         <varlistentry>
-                            <term>Usual Pencil Schur form</term>
+                            <term>通常のペンシルSchur形式</term>
                             <listitem>
                                 <para>
-                                    <literal>[As,Es] = schur(A,E)</literal> produces a quasi triangular
-                                    <literal>As</literal> matrix and a triangular <literal>Es</literal> matrix
-                                    which are the generalized Schur form of the pair <literal>A, E</literal>.
+                                    <literal>[As,Es] = schur(A,E)</literal> は,
+                                    対<literal>A, E</literal>の一般化Schur形式である
+                                    準三角行列<literal>As</literal>行列および三角行列<literal>Es</literal>
+                                    を出力します.
                                 </para>
                                 <para>
-                                    <literal>[As,Es,Q,Z] = schur(A,E)</literal>
-                                    returns in addition two unitary matrices
-                                    <literal>Q</literal> and <literal>Z</literal> such that
-                                    <literal>As=Q'*A*Z</literal> and <literal>Es=Q'*E*Z</literal>.
+                                    <literal>[As,Es,Q,Z] = schur(A,E)</literal>は,更に
+                                    <literal>As=Q'*A*Z</literal> および <literal>Es=Q'*E*Z</literal>となるような
+                                    2つのユニタリ行列<literal>Q</literal> および <literal>Z</literal>を返します.
                                 </para>
                             </listitem>
                         </varlistentry>
                         <varlistentry>
-                            <term>Ordered Schur forms:</term>
+                            <term>ソートされたSchur形式:</term>
                             <listitem>
                                 <para>
-                                    <literal>[As,Es,Z,dim] = schur(A,E,'c')</literal>
-                                    returns the real generalized
-                                    Schur form of the pencil <literal>s*E-A</literal>. In addition, the dim first columns 
-                                    of <literal>Z</literal> span a basis of the right eigenspace  associated with 
-                                    eigenvalues with negative real parts (stable "continuous
-                                    time" generalized eigenspace).
+                                    <literal>[As,Es,Z,dim] = schur(A,E,'c')</literal>は,
+                                    ペンシル<literal>s*E-A</literal>の実数一般化Schur形式を返します.
+                                    更に, <literal>Z</literal>の最初の列 dim は,
+                                    実部が負の固有値 (安定な"連続時間"一般化固有値空間)に関連する
+                                    固有値空間の基底を構成します.
                                 </para>
                                 <para>
                                     <literal>[As,Es,Z,dim] = schur(A,E,'d')</literal>
                                 </para>
                                 <para>
-                                    returns the real generalized
-                                    Schur form of the pencil <literal>s*E-A</literal>. In addition, the dim first columns 
-                                    of <literal>Z</literal> make a basis of the right eigenspace  associated with 
-                                    eigenvalues with magnitude lower than 1 (stable "discrete
-                                    time" generalized eigenspace).
+                                    は,ペンシル<literal>s*E-A</literal>の
+                                    実数一般化Schur形式を返します.
+                                    更に, <literal>Z</literal>の最初の列 dim は,
+                                    大きさ1未満の固有値 (安定な"離散時間"一般化固有値空間)に関連する
+                                    固有値空間の基底を構成します.
                                 </para>
                                 <para>
                                     <literal>[As,Es,Z,dim] = schur(A,E,extern2)</literal>
                                 </para>
                                 <para>
-                                    returns the real generalized Schur form of the pencil <literal>s*E-A</literal>. 
-                                    In addition, the dim first columns 
-                                    of <literal>Z</literal> make a basis of the right eigenspace  associated with 
-                                    eigenvalues of the pencil which are selected according to a
-                                    rule which is given by the function <literal>extern2</literal>. (see external
-                                    for details). This external can be described by a Scilab
-                                    function or by C or Fortran procedure:      
+                                    は,ペンシル<literal>s*E-A</literal>の実一般化Schur形式を返します.
+                                    更に, <literal>Z</literal>の最初の列 dim は,
+                                    関数<literal>extern2</literal>により指定された規則に基づき選択された
+                                    ペンシルの固有値に関する固有値空間の基底を構成します.
+                                    (詳細は external 参照)
+                                    この external は Scilab 関数またはCまたはFortranプロシージャ
+                                    により次のように記述することができます:
                                 </para>
                                 <variablelist>
                                     <varlistentry>
-                                        <term>A Scilab function</term>
+                                        <term>Scilab関数</term>
                                         <listitem>
                                             <para>
-                                                If <literal>extern2</literal> is described by a Scilab function, it should
-                                                have the following calling sequence:
-                                                <literal>s=extern2(Alpha,Beta)</literal>, where <literal>Alpha</literal> and
-                                                <literal>Beta</literal> defines a generalized eigenvalue and
-                                                <literal>s</literal> a boolean.
+                                                <literal>extern2</literal>がScilab関数により記述される場合,
+                                                以下の呼び出し手順を有する必要があります:
+                                                <literal>s=extern2(Alpha,Beta)</literal>, ただし <literal>Alpha</literal> および
+                                                <literal>Beta</literal> は一般化固有値および論理値 <literal>s</literal>
+                                                を定義します.
                                             </para>
                                         </listitem>
                                     </varlistentry>
                                     <varlistentry>
-                                        <term>C or Fortran procedure</term>
+                                        <term>C またはFortranプロシージャ</term>
                                         <listitem>
                                             <para>
-                                                if external <literal>extern2</literal> is described by a C or a
-                                                Fortran procedure, it should have the following calling
-                                                sequence:
+                                                if external <literal>extern2</literal> がCまたはFortran関数により
+                                                記述される場合,以下の呼び出し手順を有する必要があります:
                                             </para>
                                             <para>
                                                 <literal>int extern2(double *AlphaR, double *AlphaI, double *Beta)</literal>
                                             </para>
                                             <para>
-                                                if <literal>A</literal> and <literal>E</literal> are real and
+                                                : <literal>A</literal> および <literal>E</literal> が実数の場合.
                                             </para>
                                             <para>
                                                 <literal>int extern2(double *AlphaR, double *AlphaI, double *BetaR, double *BetaI)</literal>
                                             </para>
                                             <para>
-                                                if <literal>A</literal> or <literal>E</literal> are complex.
-                                                <literal>Alpha</literal>, and <literal>Beta</literal> defines the generalized eigenvalue.
-                                                a true or non zero returned value stands for selected generalized eigenvalue.
+                                                : <literal>A</literal> および <literal>E</literal> が複素数の場合.
+                                                <literal>Alpha</literal>, および <literal>Beta</literal> は一般化固有値を定義します.
+                                                trueまたは非ゼロの戻り値は,選択された一般化固有値を意味します.
                                             </para>
                                         </listitem>
                                     </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>References</title>
+        <title>参考</title>
         <para>
-            Matrix schur form computations are based on the Lapack routines DGEES and ZGEES.
+            行列Schur形式の計算はLapackルーチンDGEES および ZGEESに基づいています.
         </para>
         <para>
-            Pencil schur form computations are based on the Lapack routines DGGES and ZGGES.
+            ペンシルSchur形式の計算はLapackルーチンDGGES および ZGGESに基づいています.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
-//SCHUR FORM OF A MATRIX
+//行列Schur形式
 //----------------------
 A=diag([-0.9,-2,2,0.9]);X=rand(A);A=inv(X)*A*X;
 [U,T]=schur(A);T
 
 [U,dim,T]=schur(A,'c');
-T(1:dim,1:dim)      //stable cont. eigenvalues
+T(1:dim,1:dim)      //安定な連続時間固有値
 
 function t=mytest(Ev),t=abs(Ev)<0.95,endfunction
 [U,dim,T]=schur(A,mytest);
 T(1:dim,1:dim)  
 
-// The same function in C (a Compiler is required)
+// Cの同じ関数 (コンパイラが必要)
 cd TMPDIR;
 C=['int mytest(double *EvR, double *EvI) {' //the C code
    'if (*EvR * *EvR + *EvI * *EvI < 0.9025) return 1;'
@@ -325,13 +329,13 @@ C=['int mytest(double *EvR, double *EvI) {' //the C code
 mputl(C,TMPDIR+'/mytest.c')
 
 
-//build and link
+//構築/リンク
 lp=ilib_for_link('mytest','mytest.c',[],'c');
 link(lp,'mytest','c'); 
 
-//run it
+//実行
 [U,dim,T]=schur(A,'mytest');
-//SCHUR FORM OF A PENCIL
+//ペンシルのSchur形式
 //----------------------
 F=[-1,%s, 0,   1;
     0,-1,5-%s, 0;
@@ -339,15 +343,15 @@ F=[-1,%s, 0,   1;
     1, 0, 0, -2+%s];
 A=coeff(F,0);E=coeff(F,1);
 [As,Es,Q,Z]=schur(A,E);
-Q'*F*Z //It is As+%s*Es
+Q'*F*Z //これはAs+%s*Esです
 
 
 [As,Es,Z,dim] = schur(A,E,'c')
 function t=mytest(Alpha,Beta),t=real(Alpha)<0,endfunction
 [As,Es,Z,dim] = schur(A,E,mytest)
 
-//the same function in Fortran (a Compiler is required)
-ftn=['integer function mytestf(ar,ai,b)' //the fortran code
+//Fortranの同じ関数 (コンパイラが必要)
+ftn=['integer function mytestf(ar,ai,b)' //fortranコード
      'double precision ar,ai,b'
      'mytestf=0'
      'if(ar.lt.0.0d0) mytestf=1'
@@ -358,13 +362,13 @@ mputl('      '+ftn,TMPDIR+'/mytestf.f')
 lp=ilib_for_link('mytestf','mytestf.f',[],'F');
 link(lp,'mytestf','f'); 
 
-//run it
+//実行
 
 [As,Es,Z,dim] = schur(A,E,'mytestf')
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="spec">spec</link>
index 20bd852..8ce56b8 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns5="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" version="5.0-subset Scilab" xml:id="spec" xml:lang="en">
+<refentry xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svg="http://www.w3.org/2000/svg" xmlns:ns5="http://www.w3.org/1999/xhtml" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:db="http://docbook.org/ns/docbook" version="5.0-subset Scilab" xml:id="spec" xml:lang="ja">
     <refnamediv>
         <refname>spec</refname>
-        <refpurpose>eigenvalues of matrices and pencils</refpurpose>
+        <refpurpose>行列とペンシルの固有値</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>evals=spec(A)
             [R,diagevals]=spec(A)
             
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>引数</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex square matrix</para>
+                    <para>実数または複素正方行列</para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>B</term>
                 <listitem>
-                    <para>real or complex square matrix with same dimensions as
-                        <literal> A</literal>
+                    <para>
+                        <literal> A</literal>と同じ次元の実数または複素正方行列
                     </para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>evals</term>
+                
                 <listitem>
-                    <para>real or complex vector, the eigenvalues</para>
+                    <para>実数または複素ベクトル, 固有値</para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>diagevals</term>
+                
                 <listitem>
-                    <para>real or complex diagonal matrix (eigenvalues along the
-                        diagonal)
-                    </para>
+                    <para>実数または(対角項に固有値を有する)複素対角行列 </para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>alpha</term>
+                
                 <listitem>
-                    <para>real or complex vector, al./be gives the eigenvalues</para>
+                    <para>実数または複素ベクトル, al./be により固有値が得られます</para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>beta</term>
+                
                 <listitem>
-                    <para>real vector, al./be gives the eigenvalues</para>
+                    <para>実数ベクトル, al./be により固有値が得られます</para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>R</term>
+                
                 <listitem>
-                    <para>real or complex invertible square matrix, matrix right
-                        eigenvectors.
-                    </para>
+                    <para>可逆な実数または複素正方行列, 行列右固有ベクトル.</para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>L</term>
+                
                 <listitem>
-                    <para>real or complex invertible square matrix, pencil left
-                        eigenvectors.
-                    </para>
+                    <para>可逆な実数または複素正方行列, ペンシル左固有ベクトル.</para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>R</term>
+                
                 <listitem>
-                    <para>real or complex invertible square matrix, pencil right
-                        eigenvectors.
-                    </para>
+                    <para>可逆な実数または複素正方行列, ペンシル右固有ベクトル.</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
+    
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
+        
         <variablelist>
             <varlistentry>
                 <term>evals=spec(A)</term>
+                
                 <listitem>
                     <para>
-                        returns in vector <literal>evals</literal> the
-                        eigenvalues.
+                        ベクトル<literal>evals</literal> に固有値を返します.
                     </para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>[R,diagevals] =spec(A)</term>
+                
                 <listitem>
                     <para>
-                        returns in the diagonal matrix <literal>evals</literal> the
-                        eigenvalues and in <literal>R</literal> the right
-                        eigenvectors.
+                        対角行列r <literal>evals</literal> に固有値,
+                        <literal>R</literal>に固有ベクトルを返します.
                     </para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>evals=spec(A,B)</term>
+                
                 <listitem>
-                    <para>returns the spectrum of the matrix pencil A - s B, i.e. the
-                        roots of the polynomial matrix s B - A.
+                    <para>行列ペンシル A - s B のスペクトル,すなわち,
+                        多項式行列 s B - Aの根,を返します.
                     </para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>[alpha,beta] = spec(A,B)</term>
+                
                 <listitem>
                     <para>
-                        returns the spectrum of the matrix pencil <literal>A- s
-                            B
-                        </literal>
-                        ,i.e. the roots of the polynomial matrix <literal>A - s
-                            B
-                        </literal>
-                        .Generalized eigenvalues alpha and beta are so that the
-                        matrix <literal>A - alpha./beta B</literal> is a singular matrix.
-                        The eigenvalues are given by <literal>al./be</literal> and if
-                        <literal>beta(i) = 0</literal> the ith eigenvalue is at infinity.
-                        (For <literal>B = eye(A), alpha./beta</literal> is
-                        <literal>spec(A)</literal>). It is usually represented as the pair
-                        (alpha,beta), as there is a reasonable interpretation for beta=0,
-                        and even for both being zero.
+                        行列ペンシル<literal>A- s B</literal>のスペクトル,
+                        すなわち,多項式行列 <literal>A - s B</literal>の根を返します.
+                        一般化固有値 alpha と beta は行列 
+                        <literal>A - alpha./beta B</literal> が特異行列となる値です.
+                        固有値は <literal>al./be</literal> により指定され,
+                        <literal>beta(i) = 0</literal>の場合,i番目の固有値は無限大となります.
+                        (<literal>B = eye(A)</literal>の場合, <literal>alpha./beta</literal>は
+                        <literal>spec(A)</literal>となります).
+                        通常,beta=0や両方がゼロの場合に関して都合が良い解釈が存在するため,
+                        (alpha,beta)の組み合わせで表されます.
                     </para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>[alpha,beta,R] = spec(A,B)</term>
+                
                 <listitem>
-                    <para>
-                        returns in addition the matrix <literal>R</literal> of
-                        generalized right eigenvectors of the pencil.
+                    <para>上記に加えてペンシルの一般化右固有ベクトルとなる
+                        行列 <literal>R</literal>を返します.
                     </para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>[al,be,L,R] = spec(A,B)</term>
+                
                 <listitem>
                     <para>
-                        returns in addition the matrix <literal>L</literal> and
-                        <literal>R</literal> of generalized left and right eigenvectors of
-                        the pencil.
+                        上記に加えてペンシルの一般化右および左固有ベクトルである行列
+                        <literal>L</literal> および<literal>R</literal>を返します.
                     </para>
                 </listitem>
             </varlistentry>
+            
+            
             <varlistentry>
                 <term>[al,be,Z] = spec(A,E)</term>
                 <listitem>
                     <para>
-                        returns the matrix <literal>Z</literal> of right
-                        generalized eigen vectors.
+                         一般化右固有ベクトルである行列 <literal>Z</literal> を返します.
                     </para>
                 </listitem>
             </varlistentry>
+            
             <varlistentry>
                 <term>[al,be,Q,Z] = spec(A,E)</term>
                 <listitem>
                     <para>
-                        returns the matrices <literal>Q</literal>
-                        and <literal>Z</literal> of right and left generalized
-                        eigen vectors.
+                        一般化右および左固有ベクトルである行列 <literal>Q</literal>
+                        および <literal>Z</literal>を返します.
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
-        <para>For big full / sparse matrix, you can use the Arnoldi module.</para>
+        
+        <para>大きな完全 / 疎行列の場合, Arnoldi モジュールを使用することができます.</para>
     </refsection>
+    
     <refsection>
-        <title>References</title>
-        <para>Matrix eigenvalues computations are based on the Lapack
-            routines
-        </para>
+        <title>参照</title>
+        
+        <para>行列の固有値計算は Lapack ルーチンに基づいています</para>
+        
         <itemizedlist>
             <listitem>
-                <para>DGEEV and ZGEEV when the matrix are not symmetric,</para>
+                <para>行列が対称でない場合, DGEEV および ZGEEV.</para>
             </listitem>
+            
             <listitem>
-                <para>DSYEV and ZHEEV when the matrix are symmetric.</para>
+                <para>行列が対称の場合, DSYEV および ZHEEV.</para>
             </listitem>
         </itemizedlist>
-        <para>A complex symmetric matrix has conjugate offdiagonal terms and real
-            diagonal terms.
-        </para>
-        <para>Pencil eigenvalues computations are based on the Lapack routines
-            DGGEV and ZGGEV.
+        
+        <para>複素対象行列は複素共役の非対角項と実数の対角項を有します.</para>
+        
+        <para>ペンシル固有値計算は Lapack ルーチン
+            DGGEV および ZGGEVに基づいています.
         </para>
     </refsection>
+    
     <refsection>
-        <title>Real and complex matrices</title>
-        <para>It must be noticed that the type of the output variables, such as
-            evals or R for example, is not necessarily the same as the type of the
-            input matrices A and B. In the following paragraph, we analyse the type of
-            the output variables in the case where one computes the eigenvalues and
-            eigenvectors of one single matrix A.
+        <title>実数および複素行列</title>
+        
+        <para>
+            例えば evals や R のような出力変数の型は入力行列 A および B の型と
+            同じである必要はないことに注意してください.
+            以下のパラグラフでは、行列 A の固有値および固有ベクトルを
+            計算する際の出力変数の型を解析します.
         </para>
+        
         <itemizedlist>
             <listitem>
-                <para>Real A matrix</para>
+                <para>実数 A 行列</para>
+                
                 <itemizedlist>
                     <listitem>
-                        <para>Symetric</para>
-                        <para>The eigenvalues and the eigenvectors are real.</para>
+                        <para>対称</para>
+                        
+                        <para>固有値と固有ベクトルは実数.</para>
                     </listitem>
+                    
                     <listitem>
-                        <para>Not symmetric</para>
-                        <para>The eigenvalues and eigenvectors are complex.</para>
+                        <para>非対称</para>
+                        
+                        <para>固有値と固有ベクトルは複素数.</para>
                     </listitem>
                 </itemizedlist>
             </listitem>
+            
             <listitem>
-                <para>Complex A matrix</para>
+                <para>複素 A 行列</para>
+                
                 <itemizedlist>
                     <listitem>
-                        <para>Symetric</para>
-                        <para>The eigenvalues are real but the eigenvectors are
-                            complex.
-                        </para>
+                        <para>対称</para>
+                        
+                        <para>固有値は実数だが固有ベクトルは複素数.</para>
                     </listitem>
+                    
                     <listitem>
-                        <para>Not symmetric</para>
-                        <para>The eigenvalues and the eigenvectors are complex.</para>
+                        <para>非対称</para>
+                        
+                        <para>固有値,固有ベクトルは複素数.</para>
                     </listitem>
                 </itemizedlist>
             </listitem>
         </itemizedlist>
     </refsection>
+    
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
+        
         <programlisting role="example"><![CDATA[ 
 // MATRIX EIGENVALUES
 A=diag([1,2,3]);
@@ -272,8 +300,10 @@ E=rand(A);
 roots(det(A-%s*E))   //complex case
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    
+    <refsection>
+        <title>参照</title>
+        
         <simplelist type="inline">
             <member>
                 <link linkend="poly">poly</link>
index 77d0a4c..e81165e 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="sva">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="sva">
     <refnamediv>
         <refname>sva</refname>
-        <refpurpose> singular value approximation</refpurpose>
+        <refpurpose>特異値近似</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[U,s,V]=sva(A,k)
             [U,s,V]=sva(A,tol)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>引数</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>k</term>
                 <listitem>
-                    <para>integer</para>
+                    <para>整数</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>nonnegative real number</para>
+                    <para>非負の実数</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Singular value approximation.
+            特異値近似.
         </para>
         <para>
-            <literal>[U,S,V]=sva(A,k)</literal> with <literal>k</literal> an integer
-            &gt;=1, returns <literal>U,S</literal> and <literal>V</literal> such that
-            <literal>B=U*S*V'</literal> is the best L2 approximation of
-            <literal>A</literal> with rank(<literal>B</literal>)=<literal>k</literal>.
+            <literal>k</literal>を&gt;=1の整数とするとき,
+            <literal>[U,S,V]=sva(A,k)</literal> は,
+            rank(<literal>B</literal>)=<literal>k</literal>として
+            <literal>B=U*S*V'</literal>が<literal>A</literal>の最良のL2近似となる
+            ような
+            <literal>U,S</literal> および<literal>V</literal>を返します.
         </para>
         <para>
-            <literal>[U,S,V]=sva(A,tol)</literal> with <literal>tol</literal> a real
-            number, returns <literal>U,S</literal> and <literal>V</literal> such that
-            <literal>B=U*S*V'</literal> such that L2-norm of <literal>A-B</literal>
-            is at most <literal>tol</literal>.
+            実数<literal>tol</literal>を指定した<literal>[U,S,V]=sva(A,tol)</literal>は,
+            <literal>A-B</literal>のL2ノルムである<literal>B=U*S*V'</literal>の
+            最大値が<literal>tol</literal>となるような
+            <literal>U,S</literal> および <literal>V</literal> を返します.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(5,4)*rand(4,5);
 [U,s,V]=sva(A,2);
@@ -73,8 +75,8 @@ svd(B)
 clean(svd(A-B))
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="svd">svd</link>
index 105a3c8..38f7dda 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="svd">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="svd">
     <refnamediv>
         <refname>svd</refname>
-        <refpurpose>  singular value decomposition</refpurpose>
+        <refpurpose>特異値分解</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>s=svd(X)
             [U,S,V]=svd(X)
             [U,S,V]=svd(X,0) (obsolete)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>a real or complex matrix</para>
+                    <para>実数または複素行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>s</term>
                 <listitem>
-                    <para>real vector (singular values)</para>
+                    <para>実数ベクトル (特異値)</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>S</term>
                 <listitem>
-                    <para>real diagonal matrix (singular values)</para>
+                    <para>実数対角行列 (特異値)</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>U,V</term>
                 <listitem>
-                    <para>orthogonal or unitary square matrices (singular vectors).</para>
+                    <para>直交またはユニタリ正方行列(特異値).</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>real number</para>
+                    <para>実数</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>[U,S,V] = svd(X)</literal> produces a diagonal matrix
-            <literal>S</literal> , of the same dimension as <literal>X</literal> and with
-            nonnegative diagonal elements in decreasing order, and unitary
-            matrices <literal>U</literal> and <literal>V</literal> so that <literal>X = U*S*V'</literal>.
+            <literal>[U,S,V] = svd(X)</literal> は
+            <literal>X</literal> と同次元で
+            降順に非負の対角要素を有する
+            対角行列 <literal>S</literal>および
+            <literal>X = U*S*V'</literal>となる
+            ユニタリ行列 <literal>U</literal> と <literal>V</literal>
+            を出力する.
         </para>
         <para>
-            <literal>[U,S,V] = svd(X,0)</literal> produces the "economy
-            size" decomposition. If <literal>X</literal> is m-by-n with m &gt;
-            n, then only the first n columns of <literal>U</literal> are computed
-            and <literal>S</literal> is n-by-n.
+            <literal>[U,S,V] = svd(X,0)</literal> は
+            "エコノミーサイズ"分解を出力する.
+            <literal>X</literal> がm行n列 (m &gt; n)の場合,
+            <literal>U</literal> の最初のn列のみが計算され,
+            <literal>S</literal>は n行n列となる.
         </para>
         <para>
-            <literal>s= svd(X)</literal> by itself, returns a vector <literal>s</literal>
-            containing the singular values.
+            <literal>s= svd(X)</literal> は
+            特異値を含むベクトル<literal>s</literal>を返す.
         </para>
         <para>
-            <literal>[U,S,V,rk]=svd(X,tol)</literal> gives in addition <literal>rk</literal>, the numerical rank of <literal>X</literal> i.e. the number of 
-            singular values larger than <literal>tol</literal>.
+            <literal>[U,S,V,rk]=svd(X,tol)</literal> は
+            <literal>rk</literal>に加えて,
+            <literal>X</literal> の数値ランク,すなわち
+            <literal>tol</literal>より大きな特異値の数を出力する.
         </para>
         <para>
-            The default value of <literal>tol</literal> is the same as in <literal>rank</literal>.
+            <literal>tol</literal>のデフォルト値は
+            <literal>rank</literal>とのもの同じである.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 X=rand(4,2)*rand(2,4)
 svd(X)
 sqrt(spec(X*X'))
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参考</title>
         <simplelist type="inline">
             <member>
                 <link linkend="rank">rank</link>
@@ -117,10 +124,10 @@ sqrt(spec(X*X'))
         </simplelist>
     </refsection>
     <refsection>
-        <title>Used Functions</title>
+        <title>使用される関数</title>
         <para>
-            svd decompositions are based on  the Lapack routines DGESVD for
-            real matrices and  ZGESVD for the complex case.
+            svd 分解はLapackのルーチン DGESVD (実数行列の場合)および
+            ZGESVD (複素数の場合)に基づいている.
         </para>
     </refsection>
 </refentry>
index 4c6b6e2..842b061 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="givens">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="givens">
     <refnamediv>
         <refname>givens</refname>
-        <refpurpose> Givens transformation</refpurpose>
+        <refpurpose>ギブンス変換</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>U=givens(xy)
             U=givens(x,y)
             [U,c]=givens(xy)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>x,y</term>
                 <listitem>
-                    <para>two real or complex numbers</para>
+                    <para>実数または複素数</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>xy</term>
                 <listitem>
-                    <para> real or complex size 2 column vector</para>
+                    <para>実数または複素数の要素数2の列ベクトル</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>U</term>
                 <listitem>
-                    <para>2x2 unitary matrix</para>
+                    <para>2x2 ユニタリ行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>c</term>
                 <listitem>
-                    <para> real or complex size 2 column vector</para>
+                    <para>実数または複素数の要素数2の列ベクトル</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
+        <literal>xy = [x;y]</literal>として
         <para>
-            <literal>U= givens(x, y)</literal> or <literal>U = givens(xy)</literal> with <literal>xy = [x;y]</literal>
-            returns a <literal>2</literal>x<literal>2</literal> unitary matrix <literal>U</literal> such that:
+            <literal>U= givens(x, y)</literal> または <literal>U = givens(xy)</literal> 
+            は,次のような<literal>2</literal>x<literal>2</literal> の
+            ユニタリ行列 <literal>U</literal> を返します:
         </para>
         <para>
             <literal>U*xy=[r;0]=c</literal>.
         </para>
         <para>
-            Note that <literal>givens(x,y)</literal> and <literal>givens([x;y])</literal> are equivalent.
+            <literal>givens(x,y)</literal> および <literal>givens([x;y])</literal> は等価であることに
+            注意してください.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=[3,4;5,6];
 U=givens(A(:,1));
 U*A
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="qr">qr</link>
index 04113d9..3802156 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="householder">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="householder">
     <refnamediv>
         <refname>householder</refname>
-        <refpurpose> Householder orthogonal reflexion matrix</refpurpose>
+        <refpurpose>ハウスホルダー直交鏡映行列</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>u=householder(v [,w])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>v</term>
                 <listitem>
-                    <para>real or complex column vector</para>
+                    <para>実数または複素数の列ベクトル</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>w</term>
                 <listitem>
                     <para>
-                        real or complex column vector with same size as <literal>v</literal>. Default value is <literal>eye(v)</literal>
+                        <literal>v</literal>と同じ大きさの実数または複素数の列ベクトル.
+                        デフォルト値は<literal>eye(v)</literal>
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>u</term>
                 <listitem>
-                    <para>real or complex column vector</para>
+                    <para>実数または複素数の列ベクトル</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            given 2 column vectors <literal>v</literal>, <literal> w</literal> of same size, <literal>householder(v,w)</literal> returns a unitary 
-            column vector <literal>u</literal>, such that <literal> (eye()-2*u*u')*v</literal> is proportional to <literal>w</literal>.
-            <literal>(eye()-2*u*u')</literal> is the orthogonal Householder reflexion matrix .
+            同じ大きさの列ベクトル
+            <literal>v</literal>, <literal> w</literal> を指定すると, 
+            <literal>householder(v,w)</literal> は,
+            <literal> (eye()-2*u*u')*v</literal>が<literal>w</literal>に比例するような
+            ユニタリ列ベクトル<literal>u</literal>を返します.
+            <literal>(eye()-2*u*u')</literal> はハウスホルダー直交鏡映行列です.
         </para>
         <para>
-            <literal>w</literal> default value is <literal> eye(v)</literal>. In this case vector <literal> (eye()-2*u*u')*v</literal> is the 
-            vector  <literal> eye(v)*norm(v)</literal>.
+            <literal>w</literal> のデフォルト値は <literal> eye(v)</literal>です. 
+            この場合,ベクトル<literal> (eye()-2*u*u')*v</literal> はベクトル 
+            <literal> eye(v)*norm(v)</literal>です.
         </para>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="qr">qr</link>
index 0ab7a1d..14de18e 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="sqroot">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="sqroot">
     <refnamediv>
         <refname>sqroot</refname>
-        <refpurpose> W*W' hermitian factorization</refpurpose>
+        <refpurpose> W*W' エルミート分解</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>sqroot(X)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>symmetric non negative definite real or complex matrix</para>
+                    <para>対称非負定実または複素行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            returns W such that  <literal>X=W*W'</literal> (uses SVD).
+            <literal>X=W*W'</literal> となるようなWを返します(SVDを使用).
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 X=rand(5,2)*rand(2,5);X=X*X';
 W=sqroot(X)
@@ -48,8 +48,8 @@ W=sqroot(X)
 norm(W*W'-X,1)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="chol">chol</link>
index 48c89e8..d5e0369 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="colcomp">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="colcomp">
     <refnamediv>
         <refname>colcomp</refname>
-        <refpurpose> column compression, kernel, nullspace</refpurpose>
+        <refpurpose>列圧縮,カーネル,ヌル空間</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[W,rk]=colcomp(A [,flag] [,tol])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>flag</term>
                 <listitem>
-                    <para>character string</para>
+                    <para>文字列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>real number</para>
+                    <para>実数</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>W</term>
                 <listitem>
-                    <para>square non-singular matrix (change of basis)</para>
+                    <para>正方正則行列 (基底変換)</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>rk</term>
                 <listitem>
                     <para>
-                        integer (rank of <literal>A</literal>)
+                        整数 (<literal>A</literal>のランク)
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Column compression of <literal>A</literal>: <literal>Ac = A*W</literal> is 
-            column compressed i.e
+            <literal>A</literal>の列圧縮: <literal>Ac = A*W</literal> は
+            列圧縮,すなわち <literal>Ac=[0,Af]</literal> となります.
         </para>
         <para>
-            <literal>Ac=[0,Af]</literal> with <literal>Af</literal> full column rank, 
+            ただし, <literal>Af</literal> はフル列ランクを有します:
             rank(<literal>Af</literal>) = rank(<literal>A</literal>) = <literal>rk</literal>.
         </para>
         <para>
-            <literal>flag</literal> and <literal>tol</literal> are optional parameters: <literal>flag = 'qr'</literal> 
-            or <literal>'svd'</literal> (default is <literal>'svd'</literal>).
+            <literal>flag</literal> および <literal>tol</literal> は
+            オプションのパラメータ: <literal>flag = 'qr'</literal> 
+            または <literal>'svd'</literal> (デフォルトは
+            <literal>'svd'</literal>)です.
         </para>
         <para>
-            <literal>tol</literal> = tolerance parameter (of order <literal>%eps</literal> as default value).
+            <literal>tol</literal> = 許容誤差パラメータ (デフォルト値は
+            <literal>%eps</literal>のオーダー).
         </para>
         <para>
-            The <literal>ma-rk</literal> first columns of <literal>W</literal> span the kernel of <literal>A</literal> 
-            when <literal>size(A)=(na,ma)</literal>
+            <literal>W</literal>の最初の<literal>ma-rk</literal>列は,
+            <literal>size(A)=(na,ma)</literal>とするとき,
+            <literal>A</literal>のカーネルに広がります.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(5,2)*rand(2,5);
 [X,r]=colcomp(A);
 norm(A*X(:,1:$-r),1)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="rowcomp">rowcomp</link>
@@ -103,4 +107,8 @@ norm(A*X(:,1:$-r),1)
             </member>
         </simplelist>
     </refsection>
+    <refsection>
+        <title>作者</title>
+        <para>F.D.;   </para>
+    </refsection>
 </refentry>
index be5baae..f1b25a9 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="fullrf">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="fullrf">
     <refnamediv>
         <refname>fullrf</refname>
-        <refpurpose> full rank factorization</refpurpose>
+        <refpurpose>フルランク分解</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[Q,M,rk]=fullrf(A,[tol])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>real number (threshold for rank determination)</para>
+                    <para>実数 (ランク定義時の閾値)</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Q,M</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>rk</term>
                 <listitem>
                     <para>
-                        integer (rank of <literal>A</literal>)
+                        整数 (<literal>A</literal>のランク)
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Full rank factorization : <literal>fullrf</literal> returns <literal>Q</literal> and <literal>M</literal> such
-            that <literal>A = Q*M</literal>
-            with range(<literal>Q</literal>)=range(<literal>A</literal>) and ker(<literal>M</literal>)=ker(<literal>A</literal>),
-            <literal>Q</literal> full column rank , <literal>M</literal> full row rank,
-            <literal>rk = rank(A) = #columns(Q) = #rows(M)</literal>.
+            フルランク分解 : <literal>fullrf</literal> は,
+            <literal>A = Q*M</literal>となるような
+            <literal>Q</literal> および <literal>M</literal>を返します.
+            ただし,
+            range(<literal>Q</literal>)=range(<literal>A</literal>) および
+            ker(<literal>M</literal>)=ker(<literal>A</literal>),
+            <literal>Q</literal> フル列ランク , <literal>M</literal> フル行ランク,
+            <literal>rk = rank(A) = #columns(Q) = #rows(M)</literal>です.
         </para>
         <para>
-            <literal>tol</literal> is an optional real parameter (default value is <literal>sqrt(%eps)</literal>).
-            The rank <literal>rk</literal> of <literal>A</literal> is defined as the number of singular values
-            larger than <literal>norm(A)*tol</literal>.
+            <literal>tol</literal> はオプションの実数パラメータです
+            (デフォルト値は <literal>sqrt(%eps)</literal>です).
+            <literal>A</literal>のランク<literal>rk</literal>は
+            <literal>norm(A)*tol</literal>より大きな
+            特異値の数として定義されます.
         </para>
         <para>
-            If A is symmetric, <literal>fullrf</literal> returns <literal>M=Q'</literal>.
+            Aが対称の場合,
+            <literal>fullrf</literal> は <literal>M=Q'</literal>を返します.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(5,2)*rand(2,5);
 [Q,M]=fullrf(A);
@@ -78,8 +84,8 @@ norm(Q*M-A,1)
 svd([A,Y(:,1:d),Q])        //span(Q) = span(A) = span(Y(:,1:2))
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="svd">svd</link>
@@ -98,4 +104,8 @@ svd([A,Y(:,1:d),Q])        //span(Q) = span(A) = span(Y(:,1:2))
             </member>
         </simplelist>
     </refsection>
+    <refsection>
+        <title>作者</title>
+        <para>F.D.;   </para>
+    </refsection>
 </refentry>
index 1063130..70d4280 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="fullrfk">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="fullrfk">
     <refnamediv>
         <refname>fullrfk</refname>
-        <refpurpose> full rank factorization of A^k</refpurpose>
+        <refpurpose>A^kのフルランク分解</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[Bk,Ck]=fullrfk(A,k)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>k</term>
                 <listitem>
-                    <para>integer</para>
+                    <para>整数</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Bk,Ck</term>
                 <listitem>
-                    <para>real or complex matrices</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            This function computes the full rank factorization of <literal>A^k</literal> i.e.
-            <literal>Bk*Ck=A^k</literal> where <literal>Bk</literal> is full column rank and <literal>Ck</literal> full row rank.
-            One has range(<literal>Bk</literal>)=range(<literal>A^k</literal>) and ker(<literal>Ck</literal>)=ker(<literal>A^k</literal>).
+            この関数は,<literal>A^k</literal>のフルランク分解,
+            すなわち, <literal>Bk*Ck=A^k</literal> を計算します.
+            ただし, <literal>Bk</literal> は列フルランク,
+            <literal>Ck</literal>は行フルランクです.
+            range(<literal>Bk</literal>)=range(<literal>A^k</literal>) 
+            および ker(<literal>Ck</literal>)=ker(<literal>A^k</literal>)となります.
         </para>
         <para>
-            For <literal>k=1</literal>, <literal>fullrfk</literal> is equivalent to <literal>fullrf</literal>.
+            <literal>k=1</literal>の場合, <literal>fullrfk</literal> は
+            <literal>fullrf</literal>と等価になります.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(5,2)*rand(2,5);[Bk,Ck]=fullrfk(A,3);
 norm(Bk*Ck-A^3,1)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="fullrf">fullrf</link>
@@ -71,4 +75,8 @@ norm(Bk*Ck-A^3,1)
             </member>
         </simplelist>
     </refsection>
+    <refsection>
+        <title>作者</title>
+        <para>F.D (1990);   </para>
+    </refsection>
 </refentry>
index dba65dc..bf2b31a 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="im_inv">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="im_inv">
     <refnamediv>
         <refname>im_inv</refname>
-        <refpurpose> inverse image</refpurpose>
+        <refpurpose>原像</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[X,dim]=im_inv(A,B [,tol])
             [X,dim,Y]=im_inv(A,B, [,tol])
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A,B</term>
                 <listitem>
-                    <para>two real or complex matrices with equal number of columns</para>
+                    <para>同じ列の数を有する実数または複素数行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>X</term>
                 <listitem>
                     <para>
-                        orthogonal or unitary square matrix of order equal to the  number of columns of <literal>A</literal>
+                        次数が<literal>A</literal>の列の数に等しい直交またはユニタリ正方行列
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>dim</term>
                 <listitem>
-                    <para>integer (dimension of subspace)</para>
+                    <para>整数 (サブスペースの次元)</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Y</term>
                 <listitem>
                     <para>
-                        orthogonal matrix of order equal to the number of rows  of <literal>A</literal> and <literal>B</literal>.
+                        次数が<literal>A</literal>および<literal>B</literal>の行の数に等しい直交行列.
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>[X,dim]=im_inv(A,B)</literal> computes <literal>(A^-1)(B)</literal>
-            i.e vectors whose image through <literal>A</literal> are in
-            range(<literal>B</literal>)
+            <literal>[X,dim]=im_inv(A,B)</literal> は <literal>(A^-1)(B)</literal>,
+            すなわち, <literal>A</literal>への像が range(<literal>B</literal>) に
+            あるベクトルを計算します.
         </para>
         <para>
-            The <literal>dim</literal> first columns of <literal>X</literal> span
-            <literal>(A^-1)(B)</literal>
+            <literal>X</literal>の最初の列 <literal>dim</literal> は
+            <literal>(A^-1)(B)</literal>に広がっています.
         </para>
         <para>
-            <literal>tol</literal> is a threshold used to test if subspace inclusion;
-            default value is <literal>tol = 100*%eps</literal>.
-            If <literal>Y</literal> is returned, then <literal>[Y*A*X,Y*B]</literal> is partitioned as follows:
+            <literal>tol</literal> はサブ空間の取り込みを確認するために
+            閾値が使用されており,
+            そのデフォルト値は <literal>tol = 100*%eps</literal> です.
+            <literal>Y</literal> が返される時,
+            <literal>[Y*A*X,Y*B]</literal> は以下のように分割されます:
             <literal>[A11,A12;0,A22]</literal>,<literal>[B1;0]</literal>
         </para>
         <para>
-            where <literal>B1</literal> has full row rank (equals
-            <literal>rank(B)</literal>) and <literal>A22</literal> has full column rank
-            and has <literal>dim</literal> columns.
+            ただし, <literal>B1</literal>は行フルランク  (
+            <literal>rank(B)</literal>に等しい) そして <literal>A22</literal> は
+            列フルランクで <literal>dim</literal> 列となります.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=[rand(2,5);[zeros(3,4),rand(3,1)]];B=[[1,1;1,1];zeros(3,2)];
 W=rand(5,5);A=W*A;B=W*B;
@@ -87,8 +89,8 @@ svd([A*X(:,1:dim),B])   //vectors A*X(:,1:dim) belong to range(B)
 [X,dim,Y]=im_inv(A,B);[Y*A*X,Y*B]
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="rowcomp">rowcomp</link>
@@ -104,4 +106,8 @@ svd([A*X(:,1:dim),B])   //vectors A*X(:,1:dim) belong to range(B)
             </member>
         </simplelist>
     </refsection>
+    <refsection>
+        <title>作者</title>
+        <para>F. Delebecque INRIA</para>
+    </refsection>
 </refentry>
index c2627af..bd2b5a4 100644 (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" version="5.0-subset Scilab" xml:lang="en" xml:id="kernel">
     <refnamediv>
         <refname>kernel</refname>
-        <refpurpose> kernel, nullspace</refpurpose>
+        <refpurpose> カーネル, ヌル空間</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>W=kernel(A [,tol,[,flag])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>full real or complex matrix or real sparse matrix</para>
+                    <para>実数または複素数のフル行列または実数疎行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>flag</term>
                 <listitem>
                     <para>
-                        character string <literal>'svd'</literal> (default) or <literal>'qr'</literal>
+                        文字列 <literal>'svd'</literal> (デフォルト) または <literal>'qr'</literal>
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>real number</para>
+                    <para>実数</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>W</term>
                 <listitem>
-                    <para>full column rank matrix</para>
+                    <para>列フルランク行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>W=kernel(A)</literal> returns the kernel (nullspace) of <literal>A</literal>. If A has full column rank then an empty matrix [] is returned.
+            <literal>W=kernel(A)</literal> は<literal>A</literal>のカーネル (ヌル空間)を返します. 
+            A が列フルランクの場合, 空の行列 [] が返されます.
         </para>
         <para>
-            <literal>flag</literal> and <literal>tol</literal> are optional parameters: <literal>flag = 'qr'</literal> 
-            or <literal>'svd'</literal> (default is <literal>'svd'</literal>).
+            <literal>flag</literal> および <literal>tol</literal> は
+            オプションのパラメータです: <literal>flag = 'qr'</literal> 
+            または <literal>'svd'</literal> (デフォルトは <literal>'svd'</literal>).
         </para>
         <para>
-            <literal>tol</literal> = tolerance parameter (of order <literal>%eps</literal> as default value).
+            <literal>tol</literal> = 許容誤差パラメータ (デフォルト値は <literal>%eps</literal> のオーダ).
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(3,1)*rand(1,3);
 A*kernel(A)
@@ -72,8 +74,8 @@ A=sparse(A);
 clean(A*kernel(A))
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="colcomp">colcomp</link>
@@ -89,4 +91,8 @@ clean(A*kernel(A))
             </member>
         </simplelist>
     </refsection>
+    <refsection>
+        <title>作者</title>
+        <para>F.D.;   </para>
+    </refsection>
 </refentry>
index 5ae81b7..bcb8db4 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="range">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="range">
     <refnamediv>
         <refname>range</refname>
-        <refpurpose> range (span) of A^k</refpurpose>
+        <refpurpose>A^kの範囲</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[X,dim]=range(A,k)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real square matrix</para>
+                    <para>実数正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>k</term>
                 <listitem>
-                    <para>integer</para>
+                    <para>整数</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>orthonormal real matrix</para>
+                    <para>直交実数行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>dim</term>
                 <listitem>
-                    <para>integer (dimension of subspace)</para>
+                    <para>整数 (部分空間の次元)</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Computation of Range <literal>A^k</literal> ; the first dim rows of <literal>X</literal> span the
-            range of <literal>A^k</literal>. The last rows of <literal>X</literal> span the
-            orthogonal complement of the range. <literal>X*X'</literal> is the Identity matrix
+            範囲 <literal>A^k</literal>を計算します ; the first dim rows of <literal>X</literal> の
+            最初の dim 行は, <literal>A^k</literal>の範囲に広がります.
+            <literal>X</literal>の最後の行は,
+            この直交相補な範囲に広がります.
+            <literal>X*X'</literal> は単位行列です.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
-A=rand(4,2)*rand(2,4);   // 4 column vectors, 2 independent.
-[X,dim]=range(A,1);dim   // compute the range
+A=rand(4,2)*rand(2,4);   // 4 列ベクトル, 2 独立.
+[X,dim]=range(A,1);dim   // 範囲を計算
 
-y1=A*rand(4,1);          //a vector which is in the range of A
-y2=rand(4,1);            //a vector which is not  in the range of A
-norm(X(dim+1:$,:)*y1)    //the last entries are zeros, y1 is in the range of A
-norm(X(dim+1:$,:)*y2)    //the last entries are not zeros
+y1=A*rand(4,1);          //Aの範囲のベクトル
+y2=rand(4,1);            //Aの範囲にないベクトル
+norm(X(dim+1:$,:)*y1)    //最後のエントリはゼロ, y1 はAの範囲
+norm(X(dim+1:$,:)*y2)    //最後のエントリは非ゼロ
 
-I=X(1:dim,:)'            //I is a basis of the range
-coeffs=X(1:dim,:)*y1     // components of y1 relative to the I basis
+I=X(1:dim,:)'            //I が範囲の基底is a basis of the range
+coeffs=X(1:dim,:)*y1     // 基底Iに関連るy1の要素
 
 norm(I*coeffs-y1)        //check
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="fullrfk">fullrfk</link>
@@ -85,10 +87,16 @@ norm(I*coeffs-y1)        //check
         </simplelist>
     </refsection>
     <refsection>
-        <title>Used Functions</title>
+        <title>作者</title>
+        <para>F. D. INRIA ;   </para>
+    </refsection>
+    <refsection>
+        <title>使用される関数</title>
         <para>
-            The <literal>range</literal> function is based on the <link linkend="rowcomp">rowcomp</link> function
-            which uses the <link linkend="svd">svd</link> decomposition.
+            <literal>range</literal> 関数は,
+            <link linkend="svd">svd</link>分解を使用する
+            <link linkend="rowcomp">rowcomp</link> 関数
+            に基づいています.
         </para>
     </refsection>
 </refentry>
index 0f0db63..834df17 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="rowcomp">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="rowcomp">
     <refnamediv>
         <refname>rowcomp</refname>
-        <refpurpose> row compression, range</refpurpose>
+        <refpurpose>行圧縮, 範囲</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[W,rk]=rowcomp(A [,flag [,tol]])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>flag</term>
                 <listitem>
-                    <para>optional character string, with possible values
-                        <literal>'svd'</literal> or <literal>'qr'</literal>. The default value is  <literal>'svd'</literal>.
+                    <para>オプションの文字列, 指定可能な値は
+                        <literal>'svd'</literal> または <literal>'qr'</literal>です. 
+                        デフォルト値  <literal>'svd'</literal>はです.
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>optional real non negative number. The default value is 
+                    <para>オプションの非負の実数. デフォルト値は 
                         <literal>sqrt(%eps)*norm(A,1)</literal>.
                     </para>
                 </listitem>
             <varlistentry>
                 <term>W</term>
                 <listitem>
-                    <para>square non-singular matrix (change of basis)</para>
+                    <para>正方正則行列 (基底の変更)</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>rk</term>
                 <listitem>
                     <para>
-                        integer (rank of <literal>A</literal>)
+                        整数 (<literal>A</literal>のランク)
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Row compression of <literal>A</literal>. <literal>Ac = W*A</literal> is a row compressed matrix: i.e. 
-            <literal>Ac=[Af;0]</literal> with <literal>Af</literal> full row rank.
+            <literal>A</literal>の行圧縮. <literal>Ac = W*A</literal> は行圧縮された行列です: すなわち, 
+            <literal>Af</literal>を行フルランクとして
+            <literal>Ac=[Af;0]</literal> となります.
         </para>
         <para>
-            <literal>flag</literal> and <literal>tol</literal> are optional parameters: <literal>flag='qr'</literal> 
-            or <literal>'svd'</literal> (default <literal>'svd'</literal>).
+            <literal>flag</literal> および <literal>tol</literal> はオプションのパラメータです: <literal>flag='qr'</literal> 
+            または <literal>'svd'</literal> (デフォルト <literal>'svd'</literal>).
         </para>
         <para>
-            <literal>tol</literal> is a tolerance parameter.
+            <literal>tol</literal> は許容誤差パラメータです.
         </para>
         <para>
-            The <literal>rk</literal> first columns of <literal>W'</literal> span the range of
-            <literal>A</literal>.
+            <literal>W'</literal>の最初の<literal>rk</literal> 列には,
+            <literal>A</literal>の範囲が広がります.
         </para>
         <para>
-            The <literal>rk</literal> first (top) rows of <literal>W</literal> span the row
-            range of <literal>A</literal>.
+            <literal>W</literal>の最初の(上側の)<literal>rk</literal> 行には,
+            <literal>A</literal>の行範囲が広がります.
         </para>
         <para>
-            A non zero vector <literal>x</literal> belongs to range(<literal>A</literal>) iff
-            <literal>W*x</literal> is row  compressed in accordance with <literal>Ac</literal>
-            i.e the norm of its last components is small w.r.t its first
-            components.
+            非ゼロベクトル <literal>x</literal> は,
+            <literal>W*x</literal>が<literal>Ac</literal>に基づき行圧縮された場合,
+            すなわち,その最後の要素のノルムが最初の要素に対して小さい場合に限り,
+            range(<literal>A</literal>)に属します.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
-A=rand(5,2)*rand(2,4);              // 4 col. vectors, 2 independent.
+A=rand(5,2)*rand(2,4);              // 4 列ベクトル, 2 つは独立.
 [X,dim]=rowcomp(A);Xp=X';
 svd([Xp(:,1:dim),A])                //span(A) = span(Xp(:,1:dim)
-x=A*rand(4,1);                      //x belongs to span(A)
+x=A*rand(4,1);                      //x は span(A)に属します
 y=X*x  
-norm(y(dim+1:$))/norm(y(1:dim))     // small
+norm(y(dim+1:$))/norm(y(1:dim))     // 小さい
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="colcomp">colcomp</link>
@@ -114,10 +116,14 @@ norm(y(dim+1:$))/norm(y(1:dim))     // small
         </simplelist>
     </refsection>
     <refsection>
-        <title>Used Functions</title>
+        <title>作者</title>
+        <para>F. D.; INRIA   </para>
+    </refsection>
+    <refsection>
+        <title>使用される関数</title>
         <para>
-            The <literal>rowcomp</literal> function is based on the <link linkend="svd">svd</link> or
-            <link linkend="qr">qr</link> decompositions.
+            <literal>rowcomp</literal> 関数は<link linkend="svd">svd</link> または
+            <link linkend="qr">qr</link> 分解です.
         </para>
     </refsection>
 </refentry>
index ebfd0d7..e76219a 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="aff2ab">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="aff2ab">
     <refnamediv>
         <refname>aff2ab</refname>
-        <refpurpose> linear (affine) function to A,b conversion</refpurpose>
+        <refpurpose>線形 (アフィン)関数を A,b に変換</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[A,b]=aff2ab(afunction,dimX,D [,flag])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>Parameters</title>
         <variablelist>
             <varlistentry>
                 <term>afunction</term>
                 <listitem>
                     <para>
-                        a scilab function <literal> Y =fct(X,D) </literal> where <literal>X, D, Y</literal> are <literal>list</literal> of matrices
+                        scilab 関数 <literal> Y =fct(X,D) </literal> 
+                        ただし, <literal>X, D, Y</literal> は行列の <literal>list</literal>
                     </para>
                 </listitem>
             </varlistentry>
@@ -34,7 +35,8 @@
                 <term>dimX</term>
                 <listitem>
                     <para>
-                        a p x 2 integer matrix (<literal>p</literal> is the number of matrices in <literal>X</literal>)
+                        p x 2 整数行列 (<literal>p</literal> は
+                        <literal>X</literal>の行列の数)
                     </para>
                 </listitem>
             </varlistentry>
@@ -42,7 +44,7 @@
                 <term>D</term>
                 <listitem>
                     <para>
-                        a <literal>list</literal> of real matrices (or any other valid Scilab object).
+                        実数行列の<literal>list</literal>  (または任意の有効なScilab オブジェクト).
                     </para>
                 </listitem>
             </varlistentry>
                 <term>flag</term>
                 <listitem>
                     <para>
-                        optional parameter (<literal>flag='f'</literal> or <literal>flag='sp'</literal>)
+                        オプションのパラメータ (<literal>flag='f'</literal> または <literal>flag='sp'</literal>)
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>a real matrix</para>
+                    <para>実数行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>b</term>
                 <listitem>
                     <para>
-                        a real vector having same row dimension as <literal>A</literal>
+                        <literal>A</literal>と同じ行次元を有する実数ベクトル
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>aff2ab</literal>  returns the matrix representation of an affine
-            function (in the canonical basis).
+            <literal>aff2ab</literal>  はアフィン関数の(正準形式の)行列表現を返します.
         </para>
         <para>
-            <literal>afunction</literal> is a function with imposed syntax:
-            <literal> Y=afunction(X,D) </literal> where <literal> X=list(X1,X2,...,Xp) </literal> is
-            a list of p real matrices, and <literal> Y=list(Y1,...,Yq) </literal> is
-            a list of q real real matrices which depend linearly of
-            the <literal> Xi</literal>'s. The (optional) input <literal> D</literal> contains 
-            parameters needed to compute Y as a function of X. 
-            (It is generally a list of matrices).
+            <literal>afunction</literal> は以下の規定の構文を有する関数です:
+            <literal> Y=afunction(X,D) </literal> 
+            ただし, <literal> X=list(X1,X2,...,Xp) </literal> は
+            p 個の実数行列のリスト,<literal> Y=list(Y1,...,Yq) </literal> は
+            <literal> Xi</literal>に線形に依存するq 個の実数行列のリストです.
+            (オプションの) 入力 <literal> D</literal> は, X の関数として
+            Yを計算するために必要なパラメータを有しています.
         </para>
         <para>
-            <literal> dimX</literal> is a p x 2 matrix: <literal>dimX(i)=[nri,nci]</literal>
-            is the actual number of rows and columns of matrix <literal>Xi</literal>.
-            These dimensions determine <literal>na</literal>, the column dimension of 
-            the resulting matrix <literal>A</literal>: <literal>na=nr1*nc1 +...+ nrp*ncp</literal>.
+            <literal> dimX</literal> は p x 2 行列です: <literal>dimX(i)=[nri,nci]</literal>
+            は行列<literal>Xi</literal>の行と列の実際の数です.
+            これらの次元は,結果の行列<literal>A</literal>の列の次元である
+            <literal>na</literal> を以下のように定義します:
+            <literal>na=nr1*nc1 +...+ nrp*ncp</literal>.
         </para>
         <para>
-            If the optional parameter <literal>flag='sp'</literal> the resulting <literal>A</literal>
-            matrix is returned as a sparse matrix.
+            オプションのパラメータ <literal>flag='sp'</literal> が指定された場合,
+            結果の行列 <literal>A</literal>は疎行列として返されます.
         </para>
         <para>
-            This function is useful to solve a system of linear equations
-            where the unknown variables are matrices.
+            この関数は,未知変数が行列であるような
+            線形方程式のシステムを解くために有用です.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
-// Lyapunov equation solver (one unknown variable, one constraint)
+// リアプノフ方程式ソルバ (未知変数1つ, 拘束条件1つ)
 deff('Y=lyapunov(X,D)','[A,Q]=D(:);Xm=X(:); Y=list(A''*Xm+Xm*A-Q)')
 A=rand(3,3);Q=rand(3,3);Q=Q+Q';D=list(A,Q);dimX=[3,3];
 [Aly,bly]=aff2ab(lyapunov,dimX,D);
 [Xl,kerA]=linsolve(Aly,bly); Xv=vec2list(Xl,dimX); lyapunov(Xv,D)
 Xm=Xv(:); A'*Xm+Xm*A-Q
 
-// Lyapunov equation solver with redundant constraint X=X'
-// (one variable, two constraints) D is global variable
+// 冗長な拘束 t X=X'を有するリアプノフ方程式ソルバ
+// (変数1つ, 拘束条件2つt) D はグローバル変数
 deff('Y=ly2(X,D)','[A,Q]=D(:);Xm=X(:); Y=list(A''*Xm+Xm*A-Q,Xm''-Xm)')
 A=rand(3,3);Q=rand(3,3);Q=Q+Q';D=list(A,Q);dimX=[3,3];
 [Aly,bly]=aff2ab(ly2,dimX,D);
 [Xl,kerA]=linsolve(Aly,bly); Xv=vec2list(Xl,dimX); ly2(Xv,D)
 
-// Francis equations
-// Find matrices X1 and X2 such that:
+// フランシス方程式
+// 以下のような行列 X1 および X2 を見つける:
 // A1*X1 - X1*A2 + B*X2 -A3 = 0
 // D1*X1 -D2 = 0 
 deff('Y=bruce(X,D)','[A1,A2,A3,B,D1,D2]=D(:),...
@@ -131,7 +133,7 @@ dimX=[[m1,n2];[m3,m2]];
 [Xf,KerAf]=linsolve(Af,bf);Xsol=vec2list(Xf,dimX)
 bruce(Xsol,D)
 
-// Find all X which commute with A
+// Aを変換する全てのXを見つける
 deff('y=f(X,D)','y=list(D(:)*X(:)-X(:)*D(:))')
 A=rand(3,3);dimX=[3,3];[Af,bf]=aff2ab(f,dimX,list(A));
 [Xf,KerAf]=linsolve(Af,bf);[p,q]=size(KerAf);
@@ -139,8 +141,8 @@ Xsol=vec2list(Xf+KerAf*rand(q,1),dimX);
 C=Xsol(:); A*C-C*A
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="linsolve">linsolve</link>
index 05080eb..072c7cd 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="chol">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="chol">
     <refnamediv>
         <refname>chol</refname>
-        <refpurpose> Cholesky factorization</refpurpose>
+        <refpurpose> コレスキー分解</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[R]=chol(X)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>a symmetric positive definite real or complex matrix.</para>
+                    <para>実数または複素数の正定対称行列.</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            If <literal>X</literal> is positive definite, then <literal>R = chol(X)</literal> produces an upper 
-            triangular matrix <literal>R</literal> such that <literal>R'*R = X</literal>.
+            <literal>X</literal> が正定の場合, <literal>R = chol(X)</literal> は,
+            <literal>R'*R = X</literal>となるような
+            上三角行列<literal>R</literal>を出力します.
         </para>
         <para>
-            <literal>chol(X)</literal> uses only the diagonal and upper triangle of <literal>X</literal>.
-            The lower triangular is assumed to be the (complex conjugate) 
-            transpose of the upper.
+            <literal>chol(X)</literal> は<literal>X</literal>の対角項
+            と上三角部のみを使用します.
+            下三角部は上三角部の転置(複素共役)とみなされます.
         </para>
     </refsection>
     <refsection>
-        <title>References</title>
+        <title>参考文献</title>
         <para>
-            Cholesky decomposition is based on  the Lapack routines
-            DPOTRF for  real matrices and  ZPOTRF for the complex case.
+            コレスキー分解はLapackルーチン DPOTRF (実数行列の場合)および ZPOTRF (複素行列の場合)
+            に基づきます.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 W=rand(5,5)+%i*rand(5,5);
 X=W*W';
@@ -58,8 +59,8 @@ R=chol(X);
 norm(R'*R-X)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="spchol">spchol</link>
index 2da37a3..18ef505 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="inv">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="inv">
     <refnamediv>
         <refname>inv</refname>
-        <refpurpose> matrix inverse</refpurpose>
+        <refpurpose> 逆行列</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>inv(X)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>real or complex square matrix, polynomial matrix, rational matrix in transfer or state-space representation.</para>
+                    <para>実数または複素数の正方行列, 多項式行列および
+                        伝達関数または状態空間表現の有理行列.
+                    </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>inv(X)</literal> is the inverse of the square matrix <literal>X</literal>. A warning
-            message is printed if <literal>X</literal> is badly scaled or nearly singular.
+            <literal>inv(X)</literal> は正方行列 <literal>X</literal>の逆行列
+            となる. 
+            <literal>X</literal> のスケーリングが
+            悪い場合や特異行列に近い場合には警告を出力する.
         </para>
         <para>
-            For polynomial matrices or rational matrices in transfer representation,
-            <literal>inv(X)</literal> is equivalent to <literal>invr(X)</literal>.
+            多項式行列または伝達関数表現の有理行列の場合,
+            <literal>inv(X)</literal> は <literal>invr(X)</literal>に等しくなる.
         </para>
         <para>
-            For linear systems in state-space representation (<literal>syslin</literal> list),
-            <literal>invr(X)</literal> is equivalent to <literal>invsyslin(X)</literal>.
+            状態空間表現の線形システム(<literal>syslin</literal> リスト)の場合,
+            <literal>invr(X)</literal> は <literal>invsyslin(X)</literal>に等しくなる.
         </para>
     </refsection>
     <refsection>
-        <title>References</title>
+        <title>参照</title>
         <para>
-            <literal>inv</literal> function for matrices of numbers is  based on the Lapack routines
-            DGETRF, DGETRI for  real matrices and  ZGETRF, ZGETRI for the complex case.
-            For polynomial matrix and rational function matrix <literal>inv</literal> is based on the <literal>invr</literal>
-            Scilab function.
+            数値行列用の<literal>inv</literal> 関数は Lapack ルーチン
+            DGETRF, DGETRI (実数行列の場合)および  ZGETRF, ZGETRI
+            (複素数の場合)に基づいている.
+            多項式および有理行列に関する <literal>inv</literal> は
+            Scilab関数<literal>invr</literal>に基づいている.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(3,3);inv(A)*A
 
@@ -70,8 +75,8 @@ W=inv(A)*A
 clean(ss2tf(W))
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参考</title>
         <simplelist type="inline">
             <member>
                 <link linkend="slash">slash</link>
index ecf06f9..d803e2e 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="linsolve">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="linsolve">
     <refnamediv>
         <refname>linsolve</refname>
-        <refpurpose> linear equation solver</refpurpose>
+        <refpurpose>線形方程式ソルバ</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[x0,kerA]=linsolve(A,b [,x0])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
                     <para>
-                        a <literal>na x ma</literal> real matrix (possibly sparse)
+                        a <literal>na x ma</literal> 実数行列 (疎行列の場合もあり)
                     </para>
                 </listitem>
             </varlistentry>
                 <term>b</term>
                 <listitem>
                     <para>
-                        a <literal>na x 1</literal> vector (same row dimension as <literal>A</literal>)
+                        <literal>na x 1</literal>ベクトル (<literal>A</literal>の行と同じ次元)
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>x0</term>
                 <listitem>
-                    <para>a real vector</para>
+                    <para>実数ベクトル</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>kerA</term>
                 <listitem>
                     <para>
-                        a <literal>ma x k</literal> real matrix
+                        <literal>ma x k</literal> 実数行列
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>linsolve</literal>  computes all the solutions to <literal> A*x+b=0</literal>.
+            <literal>linsolve</literal>  は,
+            <literal> A*x+b=0</literal>の解を全て計算します.
         </para>
         <para>
-            <literal>x0</literal> is a particular solution (if any) and <literal> kerA= </literal>nullspace
-            of <literal>A</literal>. Any <literal>x=x0+kerA*w</literal> with arbitrary <literal>w</literal> satisfies
-            <literal> A*x+b=0</literal>.
+            <literal>x0</literal> は特解 (存在する場合),
+            <literal> kerA </literal> は<literal>A</literal>のヌル空間です.
+            任意の<literal>w</literal>について<literal>x=x0+kerA*w</literal>は,
+            <literal> A*x+b=0</literal>を満たします.
         </para>
         <para>
-            If compatible <literal>x0</literal> is given on entry, <literal>x0</literal> is returned. If not
-            a compatible <literal>x0</literal>, if any, is returned.
+            互換性のある <literal>x0</literal> がエントリに指定された場合, <literal>x0</literal>が返されます. 
+            そうでない場合,<literal>x0</literal>と互換性のあるもの(存在する場合)が返されます.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(5,3)*rand(3,8);
 b=A*ones(8,1);[x,kerA]=linsolve(A,b);A*x+b   //compatible b
@@ -80,23 +82,23 @@ A=rand(5,5);[x,kerA]=linsolve(A,b), -inv(A)*b  //x is unique
 // Benchmark with other linear sparse solver:
 [A,descr,ref,mtype] = ReadHBSparse(SCI+"/modules/umfpack/examples/bcsstk24.rsa"); 
 
-b = zeros(size(A,1),1);
+b = 0*ones(size(A,1),1);
 
 tic();
 res = umfpack(A,'\',b);
-mprintf('\ntime needed to solve the system with umfpack: %.3f\n',toc());
+printf('\ntime needed to solve the system with umfpack: %.3f\n',toc());
 
 tic();
 res = linsolve(A,b);
-mprintf('\ntime needed to solve the system with linsolve: %.3f\n',toc());
+printf('\ntime needed to solve the system with linsolve: %.3f\n',toc());
 
 tic();
 res = A\b;
-mprintf('\ntime needed to solve the system with the backslash operator: %.3f\n',toc());
+printf('\ntime needed to solve the system with the backslash operator: %.3f\n',toc());
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="inv">inv</link>
index 7a7ab9c..63359c1 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="lsq">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="lsq">
     <refnamediv>
         <refname>lsq</refname>
-        <refpurpose> linear least square problems.  </refpurpose>
+        <refpurpose>線形最小二乗問題.  </refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>X=lsq(A,B [,tol])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>Real or complex (m x n) matrix</para>
+                    <para>実数または複素数の (m x n) 行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>B</term>
                 <listitem>
-                    <para>real or complex (m x p) matrix</para>
+                    <para>実数または複素数の (m x p) 行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>positive scalar,  used to determine the effective rank of A
-                        (defined as the order of the largest leading triangular 
-                        submatrix R11 in the QR factorization with pivoting of A,
-                        whose estimated condition number &lt;= 1/tol. The tol default value is
-                        set to <literal>sqrt(%eps)</literal>.
+                    <para>Aの実効ランクを定義するために使用される正のスカラー
+                        (Aのピボット操作付きQR分解における最前部にある部分三角行列R11の次数として
+                        定義され,条件数の推定値は&lt;= 1/tolとなります.
+                        tolのデフォルト値は <literal>sqrt(%eps)</literal>に設定されます )
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>real or complex (n x p) matrix</para>
+                    <para>実数または複素数の (n x p) 行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>X=lsq(A,B)</literal> computes the minimum norm least square solution of
-            the equation <literal>A*X=B</literal>, while <literal>X=A \ B</literal> compute a least square
-            solution with at at most <literal>rank(A)</literal>  nonzero components per column.
+            <literal>X=lsq(A,B)</literal> は方程式 <literal>A*X=B</literal>の
+            最小二乗解の最小ノルムを計算します.
+            一方, <literal>X=A \ B</literal>は
+            各列に最大<literal>rank(A)</literal>個の非ゼロ要素を有する最小二乗解を計算します.
         </para>
     </refsection>
     <refsection>
-        <title>References</title>
+        <title>参考文献</title>
         <para>
-            <literal>lsq</literal> function is  based on the LApack functions DGELSY for
-            real matrices and ZGELSY for complex matrices.
+            <literal>lsq</literal> 関数はLApack 関数 DGELSY (実行列の場合)および
+            ZGELSY (複素行列の場合)に基づいています.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 //Build the data
 x=(1:10)';
@@ -93,8 +93,8 @@ X2=A\b
 [A*X1-b, A*X2-b] //the residuals are the same
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="backslash">backslash</link>
index 31d074c..309c3e0 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="lu">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="lu">
     <refnamediv>
         <refname>lu</refname>
-        <refpurpose> LU factorization with pivoting</refpurpose>
+        <refpurpose> ピボット選択付きのLU 分解</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[L,U]= lu(A)
             [L,U,E]= lu(A)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>Parameters</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex  matrix (m x n).</para>
+                    <para>実数または複素数の行列 (m x n).</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>L</term>
                 <listitem>
-                    <para> real or complex matrices  (m x min(m,n)).</para>
+                    <para> 実数または複素数の行列  (m x min(m,n)).</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>U</term>
                 <listitem>
-                    <para>real or complex matrices  (min(m,n) x n ).</para>
+                    <para>実数または複素数の行列  (min(m,n) x n ).</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>E</term>
                 <listitem>
-                    <para>a (n x n) permutation matrix.</para>
+                    <para>a (n x n) 置換行列.</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>[L,U]= lu(A)</literal> produces two matrices <literal>L</literal> and
-            <literal>U</literal> such that <literal>A = L*U</literal> with <literal>U</literal>
-            upper triangular and <literal>L</literal> a general matrix without any particular 
-            structure. In fact, the matrix <literal>A</literal> is factored as <literal>E*A=B*U</literal>
-            where the matrix <literal>B</literal> is lower triangular 
-            and the matrix <literal>L</literal> is computed from <literal>L=E'*B</literal>.
+            <literal>[L,U]= lu(A)</literal> は,
+            <literal>U</literal>を上三角行列,
+            <literal>L</literal>を何らかの特別な構造を持たない一般的な行列として,
+            <literal>A = L*U</literal> となるような
+            2つの行列 <literal>L</literal> および
+            <literal>U</literal> を出力します.
+            実際は,行列<literal>A</literal>は<literal>E*A=B*U</literal>
+            のように分解されます.
+            ただし, 行列<literal>B</literal>は下三角行列,
+            行列<literal>L</literal>は<literal>L=E'*B</literal>から計算されます.
         </para>
         <para>
-            If <literal>A</literal> has rank <literal>k</literal>, rows <literal>k+1</literal> to
-            <literal>n</literal> of <literal>U</literal> are zero.
+            <literal>A</literal> がランク <literal>k</literal>を有している場合, 
+            <literal>U</literal>の行 <literal>k+1</literal> から
+            <literal>n</literal> までは 0 となります.
         </para>
         <para>
-            <literal>[L,U,E]= lu(A)</literal> produces three matrices <literal>L</literal>, <literal>U</literal> and
-            <literal>E</literal> such that <literal>E*A = L*U</literal> with
-            <literal>U</literal> upper triangular and <literal>E*L</literal> lower
-            triangular for a permutation matrix <literal>E</literal>.
+            <literal>[L,U,E]= lu(A)</literal> は,
+            上三角行列<literal>U</literal>および
+            置換行列を <literal>E</literal>とした下三角行列 <literal>E*L</literal>,
+            により<literal>E*A = L*U</literal>となるような
+            3つの行列 <literal>L</literal>, <literal>U</literal> および
+            <literal>E</literal>を出力します.
         </para>
         <para>
-            If <literal>A</literal> is a real matrix, using the function
-            <literal>lufact</literal> and  <literal>luget</literal> it is possible to obtain
-            the permutation matrices and also when <literal>A</literal> is not full
-            rank the column compression of the matrix <literal>L</literal>.
+            <literal>A</literal> が実数行列の場合, 
+            関数<literal>lufact</literal> および  <literal>luget</literal>を
+            用いることにより,
+            置換行列を得ることができます.
+            <literal>A</literal>がフルランクでない場合,行列 <literal>L</literal>
+            の列圧縮も得ることができる.
         </para>
     </refsection>
     <refsection>
-        <title>Example #1</title>
+        <title>例 #1</title>
         <para>
-            In the following example, we create the Hilbert matrix of size 4 and
-            factor it with A=LU. Notice that the matrix L is not lower triangular.
-            To get a lower triangular L matrix, we should have given the 
-            output argument E to Scilab.
+            以下の例では,大きさ4のヒルバート行列を作成し,
+            A=LU と分解します.
+            行列 L は下三角行列ではないことに注意してください.
+            下三角行列Lを取得するには,
+            出力引数 E を Scilab に指定する必要があります.
         </para>
         <programlisting role="example"><![CDATA[ 
 a = testmatrix("hilb",4);
@@ -93,10 +103,11 @@ norm(l*u-a)
  ]]></programlisting>
     </refsection>
     <refsection>
-        <title>Example #2</title>
+        <title>例 #2</title>
         <para>
-            In the following example, we create the Hilbert matrix of size 4 and
-            factor it with EA=LU. Notice that the matrix L is lower triangular.
+            以下の例では,大きさ4のヒルバート行列を作成し,
+            EA=LU と分解します.
+            行列 L は下三角行列であることに注意してください.
         </para>
         <programlisting role="example"><![CDATA[ 
 a = testmatrix("hilb",4);
@@ -105,9 +116,10 @@ norm(l*u-e*a)
  ]]></programlisting>
     </refsection>
     <refsection>
-        <title>Example #3</title>
+        <title>例 #3</title>
         <para>
-            The following example shows how to use the lufact and luget functions.
+            以下の例では, lufact および luget 関数を使用する
+            方法を示しています.
         </para>
         <programlisting role="example"><![CDATA[ 
 a=rand(4,4);
@@ -124,8 +136,8 @@ Q=full(Q);
 norm(P*L*U*Q-a)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="lufact">lufact</link>
@@ -145,10 +157,10 @@ norm(P*L*U*Q-a)
         </simplelist>
     </refsection>
     <refsection>
-        <title>Used Functions</title>
+        <title>使用する関数</title>
         <para>
-            lu decompositions are based on the Lapack routines DGETRF for real
-            matrices and ZGETRF for the complex case.
+            lu 分解 Lapack ルーチン DGETRF (実数行列の場合)
+            および ZGETRF (複素数の場合) に基づいています.
         </para>
     </refsection>
 </refentry>
index 820ddc1..c9a7880 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="pinv">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="pinv">
     <refnamediv>
         <refname>pinv</refname>
-        <refpurpose> pseudoinverse</refpurpose>
+        <refpurpose>擬似逆行列</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>pinv(A,[tol])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>real number</para>
+                    <para>実数</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>X= pinv(A)</literal> produces a matrix <literal>X</literal> of the
-            same dimensions as <literal>A'</literal> such that:
+            <literal>X= pinv(A)</literal> は,
+            <literal>A'</literal>と同じ次元の以下のような
+            行列<literal>X</literal>を出力します:
         </para>
         <para>
-            <literal>A*X*A = A, X*A*X = X</literal>  and both
-            <literal>A*X</literal> and <literal>X*A</literal> are Hermitian .
+            <literal>A*X*A = A, X*A*X = X</literal>  そして
+            <literal>A*X</literal> および <literal>X*A</literal>
+            はエルミート行列です.
         </para>
         <para>
-            The computation is  based  on SVD and  any  singular values 
-            lower than a tolerance are treated   as zero: this  tolerance 
-            is accessed by <literal>X=pinv(A,tol)</literal>.
+            計算は特異値分解に基づいており,
+            許容値よりも小さい特異値は 0 として扱われます:
+            この許容誤差は <literal>X=pinv(A,tol)</literal>
+            でアクセスされます.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(5,2)*rand(2,4);
 norm(A*pinv(A)*A-A,1)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="rank">rank</link>
@@ -74,10 +77,10 @@ norm(A*pinv(A)*A-A,1)
         </simplelist>
     </refsection>
     <refsection>
-        <title>Used Functions</title>
+        <title>使用される関数</title>
         <para>
-            <literal>pinv</literal> function is  based on the singular value decomposition
-            (Scilab function <literal>svd</literal>).
+            <literal>pinv</literal> 関数は特異値分解に基づいています
+            (Scilab関数 <literal>svd</literal>).
         </para>
     </refsection>
 </refentry>
index 6f24c66..26e800e 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="qr">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="qr">
     <refnamediv>
         <refname>qr</refname>
-        <refpurpose> QR decomposition</refpurpose>
+        <refpurpose> QR 分解</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[Q,R]=qr(X [,"e"])
             [Q,R,E]=qr(X [,"e"])
             [Q,R,rk,E]=qr(X [,tol])
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>nonnegative real number</para>
+                    <para>非負の実数</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Q</term>
                 <listitem>
-                    <para>square orthogonal or unitary matrix</para>
+                    <para>正方直交またはユニタリ行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>R</term>
                 <listitem>
                     <para>
-                        matrix with same dimensions as <literal>X</literal>
+                        <literal>X</literal>と同じ次元の行列
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>E</term>
                 <listitem>
-                    <para>permutation matrix</para>
+                    <para>置換行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>rk</term>
                 <listitem>
                     <para>
-                        integer (QR-rank of <literal>X</literal>)
+                        整数 (<literal>X</literal>のQRランク)
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <variablelist>
             <varlistentry>
                 <term>[Q,R] = qr(X)</term>
                 <listitem>
                     <para>
-                        produces an upper triangular matrix <literal>R</literal> of the same dimension as <literal>X</literal> and an orthogonal (unitary in the complex case) matrix <literal>Q</literal> so that <literal>X = Q*R</literal>. <literal>[Q,R] = qr(X,"e")</literal> produces an "economy size": If <literal>X</literal> is m-by-n with m &gt; n, then only the first n columns of <literal>Q</literal>  are computed as well as the first n rows of <literal>R</literal>.
+                        <literal>X = Q*R</literal>となるような
+                        <literal>X</literal>と同じ次元の
+                        上三角行列<literal>R</literal>および直交(複素数の場合はユニタリ)行列
+                        <literal>Q</literal>を出力します.
+                        <literal>[Q,R] = qr(X,"e")</literal>は次にように
+                        "エコノミーサイズ"で出力します:
+                        <literal>X</literal> が m行n列 (m &gt; n)の場合,
+                        <literal>Q</literal>の最初のn列のみが
+                        <literal>R</literal>の最初のn行と同時に計算されます.
                     </para>
                     <para>
-                        From <literal>Q*R = X</literal> , it follows that
-                        the kth column of the matrix <literal>X</literal>, is expressed as a linear combination
-                        of the k first columns of <literal>Q</literal> (with coefficients <literal> R(1,k), ..., R(k,k) </literal>). The  k first columns of <literal>Q</literal> make an orthogonal basis
-                        of the subspace spanned by the k first comumns of <literal>X</literal>. If column <literal>k</literal>
-                        of <literal>X</literal> (i.e. <literal>X(:,k)</literal> ) is a linear combination of the first 
-                        <literal>p</literal> columns of <literal>X</literal>, then the entries <literal>R(p+1,k), ..., R(k,k)</literal>
-                        are zero. It this situation, <literal>R</literal> is upper trapezoidal. If <literal>X</literal> has
-                        rank <literal>rk</literal>, rows <literal>R(rk+1,:), R(rk+2,:), ...</literal> are zeros.
+                        <literal>Q*R = X</literal> から,
+                        行列 <literal>X</literal>のk番目の列は,
+                        (係数 <literal> R(1,k), ..., R(k,k) </literal>を用いて)
+                        <literal>Q</literal>の最初のk列の線形結合で表されます. 
+                        <literal>Q</literal>の最初のk列は,<literal>X</literal>の最初のk列
+                        に広がる部分空間の直交基底を作成します.
+                        <literal>X</literal>の列<literal>k</literal>(すなわち, <literal>X(:,k)</literal> )
+                        が<literal>X</literal>の最初の<literal>p</literal>列の線形結合の場合,
+                        エントリ<literal>R(p+1,k), ..., R(k,k)</literal>は 0 となります.
+                        この場合,<literal>R</literal>は上台形となります.
+                        <literal>X</literal> がランク<literal>rk</literal>を有する場合,
+                        行 <literal>R(rk+1,:), R(rk+2,:), ...</literal> は 0 となります.
                     </para>
                 </listitem>
             </varlistentry>
                 <term>[Q,R,E] = qr(X)</term>
                 <listitem>
                     <para>
-                        produces a (column) permutation matrix <literal>E</literal>, an upper
-                        triangular <literal>R</literal> with decreasing diagonal elements and an
-                        orthogonal (or unitary) <literal>Q</literal> so that <literal>X*E =    Q*R</literal>. 
-                        If <literal>rk</literal> is the rank of <literal>X</literal>, the
-                        <literal>rk</literal> first  entries along the main diagonal of
-                        <literal>R</literal>, i.e. <literal>R(1,1), R(2,2), ..., R(rk,rk)</literal>
-                        are all different from zero.  <literal>[Q,R,E] =  qr(X,"e")</literal> 
-                        produces an "economy size":
-                        If <literal>X</literal> is m-by-n with m &gt; n, then only the first n
-                        columns of <literal>Q</literal>  are computed as well as the first n
-                        rows of <literal>R</literal>. 
+                        <literal>X*E =    Q*R</literal>となるような
+                        (列)置換行列<literal>E</literal>,
+                        降順の対角要素を有する上三角行列 <literal>R</literal>,
+                        直交(またはユニタリ)<literal>Q</literal>
+                        を出力します.
+                        <literal>rk</literal>が<literal>X</literal>のランクの場合,
+                        <literal>R</literal>の主対角項に沿った
+                        最初の<literal>rk</literal>個のエントリ,
+                        すなわち,<literal>R(1,1), R(2,2), ..., R(rk,rk)</literal>は
+                        全て0以外となります.
+                        <literal>[Q,R,E] =  qr(X,"e")</literal> は
+                        "エコノミーサイズ"で出力します:
+                        <literal>X</literal> が m行n列 (m &gt; n)の場合,
+                        <literal>Q</literal>の最初のn列のみが
+                        <literal>R</literal>の最初のn行と同時に計算されます.
                     </para>
                 </listitem>
             </varlistentry>
                 <term>[Q,R,rk,E] = qr(X ,tol)</term>
                 <listitem>
                     <para>
-                        returns <literal>rk</literal> = rank estimate of <literal>X</literal> i.e. <literal>rk</literal> is the number of diagonal elements in <literal>R</literal> which are larger than a given threshold <literal>tol</literal>.
+                        <literal>rk</literal> = <literal>X</literal>のランクの推定値
+                        を返します.
+                        すなわち, <literal>rk</literal>は,
+                        指定した閾値<literal>tol</literal>より大きな
+                        <literal>R</literal>の対角要素の数となります.
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>[Q,R,rk,E] = qr(X) </term>
                 <listitem>
+                    
+                    
                     <para>
-                        returns <literal>rk</literal> = rank estimate of <literal>X</literal>
-                        i.e. <literal>rk</literal> is the number of diagonal elements in
-                        <literal>R</literal> which are larger than
-                        <literal>tol=R(1,1)*%eps*max(size(R))</literal>. See <literal>rankqr</literal>
-                        for a rank revealing QR factorization, using the condition number
-                        of <literal>R</literal>.
+                        <literal>rk</literal> = <literal>X</literal>のランクの推定値
+                        を返します.
+                        すなわち,<literal>rk</literal> は
+                        <literal>tol=R(1,1)*%eps*max(size(R))</literal>より大きな
+                        <literal>R</literal>の対角要素の数となります.
+                        <literal>R</literal>の条件数を用いる
+                        ランク計算型のQR分解については,<literal>rankqr</literal>を
+                        参照してください.
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 // QR factorization, generic case
 // X is tall (full rank)
@@ -153,8 +177,8 @@ norm(Q'*A-R)
 svd([A,Q(:,1:rk)])    //span(A) =span(Q(:,1:rk))
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="rankqr">rankqr</link>
@@ -174,11 +198,11 @@ svd([A,Q(:,1:rk)])    //span(A) =span(Q(:,1:rk))
         </simplelist>
     </refsection>
     <refsection>
-        <title>Used Functions</title>
+        <title>使用する関数</title>
         <para>
-            qr decomposition is based  the Lapack routines DGEQRF, DGEQPF,
-            DORGQR for the real matrices and  ZGEQRF, ZGEQPF, ZORGQR for the
-            complex case.
+            qr 分解はLapack ルーチン DGEQRF, DGEQPF,
+            DORGQR (実数行列)および  ZGEQRF, ZGEQPF, ZORGQR (複素数の場合)
+            に基づいています.
         </para>
     </refsection>
 </refentry>
index 0be1d12..f0a4b10 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="rankqr">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="rankqr">
     <refnamediv>
         <refname>rankqr</refname>
-        <refpurpose>  rank revealing QR factorization</refpurpose>
+        <refpurpose>QR分解に基づく階数</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[Q,R,JPVT,RANK,SVAL]=rankqr(A, [RCOND,JPVT])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>RCOND</term>
                 <listitem>
-                    <para>real number used to determine the effective rank of
-                        <literal>A</literal>, which is defined as the order of the largest leading
-                        triangular submatrix <literal>R11</literal> in the QR factorization with
-                        pivoting of<literal>A</literal>, whose estimated condition number &lt;
-                        <literal>1/RCOND</literal>.
+                    <para>
+                        <literal>A</literal>の実効階数(ランク)を定義するために使用される実数です.
+                        この階数は,
+                        <literal>A</literal>のピボット選択付きのQR分解の中の
+                        最大の先頭の部分三角行列<literal>R11</literal>の次数として定義されます.
+                        その推定された条件数は &lt; <literal>1/RCOND</literal> となります.
                     </para>
                 </listitem>
             </varlistentry>
                 <term>JPVT</term>
                 <listitem>
                     <para>
-                        integer vector on entry, if <literal>JPVT(i)</literal> is not 0, the
-                        <literal>i</literal>-th column of <literal> A</literal> is permuted to the front
-                        of <literal>AP</literal>, otherwise column <literal>i</literal> is a free
-                        column. On exit, if <literal>JPVT(i) = k</literal>, then the
-                        <literal>i</literal>-th column of <literal>A*P</literal> was the
-                        <literal>k</literal>-th column of <literal>A</literal>. 
+                        エントリの整数ベクトル, <literal>JPVT(i)</literal> が 0でない場合,
+                        <literal> A</literal>の<literal>i</literal>列目は
+                        <literal>AP</literal>の先頭と交換され,
+                        それ以外の場合,<literal>i</literal>は自由な列となります.
+                        処理終了時に<literal>JPVT(i) = k</literal>の場合,
+                        <literal>A*P</literal>の<literal>i</literal>列目は,
+                        <literal>A</literal>の<literal>k</literal>列目となっています.
                     </para>
                 </listitem>
             </varlistentry>
                 <term>RANK</term>
                 <listitem>
                     <para>
-                        the effective rank of <literal>A</literal>, i.e., the order of the
-                        submatrix <literal>R11</literal>.  This is the same as the order of the
-                        submatrix <literal>T1</literal> in the complete orthogonal factorization
-                        of <literal>A</literal>.
+                        <literal>A</literal>の実効ランク,すなわち,
+                        部分行列<literal>R11</literal>の次数.
+                        これは,<literal>A</literal>の完全な直交分解における
+                        部分行列<literal>T1</literal>の次数と同じです.
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>SVAL</term>
                 <listitem>
-                    <para>real vector with 3 components; The estimates of some of the
-                        singular values of the triangular factor <literal>R</literal>.
+                    <para>
+                        3つの要素を有する実数ベクトル;三角分解<literal>R</literal>の
+                        特異値の推定値.
                     </para>
                     <para>
-                        <literal>SVAL(1)</literal> is the largest singular value of
-                        <literal>R(1:RANK,1:RANK)</literal>;
+                        <literal>SVAL(1)</literal> は,
+                        <literal>R(1:RANK,1:RANK)</literal>の最大特異値です;
                     </para>
                     <para>
-                        <literal>SVAL(2)</literal> is the
-                        smallest singular value of <literal>R(1:RANK,1:RANK)</literal>;
+                        <literal>SVAL(2)</literal> は,
+                        <literal>R(1:RANK,1:RANK)</literal>の最小特異値です;
                     </para>
                     <para>
-                        <literal>SVAL(3)</literal> is the smallest singular value of
-                        <literal>R(1:RANK+1,1:RANK+1)</literal>, if <literal>RANK</literal> &lt; <literal>MIN(M,N)</literal>, 
-                        or of <literal>R(1:RANK,1:RANK)</literal>, otherwise.
+                        <literal>SVAL(3)</literal> は,
+                        <literal>RANK</literal> &lt; <literal>MIN(M,N)</literal>の場合,
+                        <literal>R(1:RANK+1,1:RANK+1)</literal>,
+                        そうでない場合, <literal>R(1:RANK,1:RANK)</literal>の最小特異値です.
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            To compute (optionally) a rank-revealing QR factorization of a real
-            general M-by-N real or complex matrix <literal>A</literal>, which may be
-            rank-deficient, and estimate its effective rank using incremental
-            condition estimation.
+            実数または複素数のM行N列一般行列<literal>A</literal>の(オプションで)
+            ランク出力を伴なうQR分解を計算します.
+            ランクが不完全になる可能性があり,実効ランクを条件数のインクリメンタル推定により
+            推定します.
         </para>
         <para>
-            The routine uses a QR factorization with column pivoting:
+            このルーチンは列ピボット選択付きのQR分解を使用します:
         </para>
-        <programlisting role=""><![CDATA[ 
+        <programlisting role = ""><![CDATA[ 
 A * P = Q * R,  where  R = [ R11 R12 ],
                            [  0  R22 ]
  ]]></programlisting>
         <para>
-            with <literal>R11</literal> defined as the largest leading submatrix whose
-            estimated condition number is less than <literal>1/RCOND</literal>.  The
-            order of <literal>R11</literal>, <literal>RANK</literal>, is the effective rank of
-            <literal>A</literal>.
+            <literal>R11</literal>は,条件数の推定値が<literal>1/RCOND</literal>未満となる
+            最大の部分行列として定義されます.
+            <literal>R11</literal>, <literal>RANK</literal>の次数は,
+            <literal>A</literal>の実効階数です.
         </para>
         <para>
-            If the triangular factorization is a rank-revealing one (which will be
-            the case if the leading columns were well- conditioned), then
-            <literal>SVAL(1)</literal> will also be an estimate for the largest singular
-            value of <literal>A</literal>, and <literal>SVAL(2)</literal> and
-            <literal>SVAL(3)</literal> will be estimates for the <literal>RANK</literal>-th
-            and <literal>(RANK+1)</literal>-st singular values of <literal>A</literal>,
-            respectively.
+            三角分解が階数出力を伴なう場合 (これは先頭の列が健全(well-conditioned)な場合です),
+            <literal>SVAL(1)</literal>は<literal>A</literal>の最大特異値の
+            推定値となり,<literal>SVAL(2)</literal> および
+            <literal>SVAL(3)</literal>は,それぞれ <literal>A</literal>の
+            <literal>RANK</literal>番目および<literal>(RANK+1)</literal>番目の
+            特異値の推定値となります.
         </para>
         <para>
-            By examining these values, one can confirm that the
-            rank is well defined with respect to the chosen value of
-            <literal>RCOND</literal>.  The ratio <literal>SVAL(1)/SVAL(2)</literal> is an
-            estimate of the condition number of <literal>R(1:RANK,1:RANK)</literal>.
+            これらの値を評価することにより,選択した<literal>RCOND</literal>の
+            値により階数が良好に定義されることを確認することができます.
+            比 <literal>SVAL(1)/SVAL(2)</literal> は,
+            <literal>R(1:RANK,1:RANK)</literal>の条件数の推定値です.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(5,3)*rand(3,7);
 [Q,R,JPVT,RANK,SVAL]=rankqr(A,%eps)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="qr">qr</link>
@@ -142,7 +145,7 @@ A=rand(5,3)*rand(3,7);
         </simplelist>
     </refsection>
     <refsection>
-        <title>Used Functions</title>
+        <title>使用される関数</title>
         <para>
             Slicot library routines MB03OD, ZB03OD.
         </para>
index d568bb3..db8c966 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="classmarkov">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="classmarkov">
     <refnamediv>
         <refname>classmarkov</refname>
-        <refpurpose> recurrent and transient classes of Markov matrix</refpurpose>
+        <refpurpose>マルコフ行列の再帰的(recurrent)および一時的(transient)なクラス</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[perm,rec,tr,indsRec,indsT]=classmarkov(M)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>M</term>
                 <listitem>
-                    <para>real N x N Markov matrix. Sum of entries in each row should add to one.</para>
+                    <para>実数 N x N マルコフ行列. 各行のエントリの合計を
+                        1に加えたもの
+                    </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>perm</term>
                 <listitem>
-                    <para>integer permutation vector.</para>
+                    <para>整数置換ベクトル.</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>rec, tr</term>
                 <listitem>
-                    <para>integer vector, number (number of states in each recurrent classes, number of transient states).</para>
+                    <para>整数ベクトル, 数値 (各再帰的クラスにおける状態量の数,
+                        一時的な状態量の数).
+                    </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>indsRec,indsT</term>
                 <listitem>
-                    <para>integer vectors. (Indexes of recurrent and transient states).</para>
+                    <para>整数ベクトル. (再帰的および一時的な状態量の添字).</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Returns a permutation vector <literal>perm</literal> such that
+            以下のような置換ベクトル<literal>perm</literal>を返します
         </para>
-        <programlisting role=""><![CDATA[ 
+        <programlisting role = ""><![CDATA[ 
 M(perm,perm) = [M11 0 0 0 0   0]
                [0 M22 0 0     0]
                [0 0 M33       0]
@@ -62,25 +66,27 @@ M(perm,perm) = [M11 0 0 0 0   0]
                [* *        *  Q]
  ]]></programlisting>
         <para>
-            Each <literal>Mii</literal> is a Markov matrix of dimension <literal>rec(i)  i=1,..,r</literal>.
-            <literal>Q</literal> is sub-Markov matrix of dimension <literal>tr</literal>.
-            States 1 to sum(rec) are recurrent and states from r+1 to n
-            are transient. 
-            One has <literal>perm=[indsRec,indsT]</literal> where indsRec is a  vector of size sum(rec) 
-            and indsT is a vector of size tr.
+            各 <literal>Mii</literal> は<literal>rec(i)  i=1,..,r</literal>次の
+            マルコフ行列です.
+            <literal>Q</literal> は<literal>tr</literal>次のサブマルコフ行列です.
+            1 から sum(rec)の状態量は再帰的で,
+            r+1からnは一時的な状態量です.
+            <literal>perm=[indsRec,indsT]</literal>となります.
+            ただし, indsRec は大きさ sum(rec)のベクトル,
+            indsT は大きさ trのベクトルです.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
-//P has two recurrent classes (with 2 and 1 states) 2 transient states
+//P は2つの再帰的なクラス (2および1個の状態量を有する) 2つの一時的な状態量
 P=genmarkov([2,1],2,'perm')
 [perm,rec,tr,indsRec,indsT]=classmarkov(P);
 P(perm,perm)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="genmarkov">genmarkov</link>
index 482e3f3..6dbef94 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="eigenmarkov">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="eigenmarkov">
     <refnamediv>
         <refname>eigenmarkov</refname>
-        <refpurpose> normalized left and right Markov eigenvectors</refpurpose>
+        <refpurpose>正規化された左および右マルコフ固有ベクトル</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[M,Q]=eigenmarkov(P)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>P</term>
                 <listitem>
-                    <para>real N x N Markov matrix. Sum of entries in each row should add to one.</para>
+                    <para>実数 N x N マルコフ行列. 1に加える各行のエントリの合計.</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>M</term>
                 <listitem>
-                    <para>real matrix with N columns.</para>
+                    <para>N個の列を有する実数行列.</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Q</term>
                 <listitem>
-                    <para>real matrix with N rows.</para>
+                    <para>N個の行を有する実数行列.</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Returns normalized left and right eigenvectors
-            associated with the eigenvalue 1 of the Markov transition matrix P.
-            If the multiplicity of this eigenvalue is m and P
-            is N x N, M is a m x N matrix and Q a N x m matrix.
-            M(k,:) is the probability distribution vector associated with the kth
-            ergodic set (recurrent class). M(k,x) is zero if x is not in the
-            k-th recurrent class.
-            Q(x,k) is the probability to end in the k-th recurrent class starting
-            from x. If <literal>P^k</literal> converges for large <literal>k</literal> (no eigenvalues on the
-            unit circle except 1), then the limit is <literal>Q*M</literal> (eigenprojection).
+            マルコフ推移行列 P の固有値 1 に関連する
+            正規化された左および右固有ベクトルを返します.
+            この固有値の多重度が m で, Pが N x N の場合,
+            M は m x N 行列で Q は N x m 行列となります.
+            M(k,:) はk番目のエルゴード集合(再帰的クラス)に関連する
+            確率分布ベクトルです.
+            M(k,x) は x が k番目の再帰的クラスにない場合には
+            0となります.
+            Q(x,k) はx から始まる k 番目の再帰的クラスに最終的にある確率です.
+            大きな<literal>k</literal>に関して<literal>P^k</literal> が
+            収束する場合(1以外に単位円上に固有値がない),
+            極限は<literal>Q*M</literal>となります(固有投影).
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
-//P has two recurrent classes (with 2 and 1 states) 2 transient states
+//P は2つの再帰的なクラス (2および1個の状態量を有する) 2つの一時的な状態量
 P=genmarkov([2,1],2) 
 [M,Q]=eigenmarkov(P);
 P*Q-Q
 Q*M-P^20
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="genmarkov">genmarkov</link>
index 7b138fb..de43302 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="genmarkov">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="genmarkov">
     <refnamediv>
         <refname>genmarkov</refname>
-        <refpurpose> generates random markov matrix with recurrent and transient classes</refpurpose>
+        <refpurpose>
+            再帰的および一時的なクラスを有するランダムなマルコフ行列を生成する
+        </refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>M=genmarkov(rec,tr)
             M=genmarkov(rec,tr,flag)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>rec</term>
                 <listitem>
-                    <para>integer row vector (its dimension is the number of recurrent classes).</para>
+                    <para>整数行ベクトル (次元は再帰的クラスの数).</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tr</term>
                 <listitem>
-                    <para>integer (number of transient states)</para>
+                    <para>整数 (一時的な状態量の数)</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>M</term>
                 <listitem>
-                    <para>real Markov matrix. Sum of entries in each row should add to one.</para>
+                    <para>実数のマルコフ行列. 
+                        1に追加する各行のエントリの合計.
+                    </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>flag</term>
                 <listitem>
                     <para>
-                        string <literal>'perm'</literal>. If given, a random permutation of the states is done.
+                        文字列 <literal>'perm'</literal>. 指定した場合,
+                        状態量のランダムな置換が行われます.
                     </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Returns in M a random Markov transition probability matrix
-            with <literal>size(rec,1)</literal> recurrent classes with <literal>rec(1),...rec($)</literal> 
-            entries respectively and tr transient states.
+            それぞれ<literal>rec(1),...rec($)</literal>個のエントリを有する
+            <literal>size(rec,1)</literal>個の再帰的なクラスとtr個の一時的な状態量を有する
+            ランダムなマルコフ推移確率行列をMに返します.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
-//P has two recurrent classes (with 2 and 1 states) 2 transient states
+//P は2つの再帰的クラス (状態量を2個及び1個有する)と 2つの遷移状態量を有します
 P=genmarkov([2,1],2,'perm')
 [perm,rec,tr,indsRec,indsT]=classmarkov(P);
 P(perm,perm)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="classmarkov">classmarkov</link>
index de19ad2..0810840 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="cond">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="cond">
     <refnamediv>
         <refname>cond</refname>
-        <refpurpose> condition number</refpurpose>
+        <refpurpose> 条件数</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>cond(X)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Condition number in 2-norm.  <literal>cond(X)</literal> is the  ratio  of  the
-            largest singular value of  <literal>X</literal>  to the smallest.
+            2乗ノルムの条件数.<literal>cond(X)</literal>は<literal>X</literal>の
+            最大特異値と最小特異値の比である.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=testmatrix('hilb',6);
 cond(A)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参考</title>
         <simplelist type="inline">
             <member>
                 <link linkend="rcond">rcond</link>
index a649899..03f5be1 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="det">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="det">
     <refnamediv>
         <refname>det</refname>
-        <refpurpose> determinant</refpurpose>
+        <refpurpose>行列式</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼出し手順</title>
         <synopsis>det(X)
             [e,m]=det(X)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>real or complex square matrix, polynomial or rational matrix.</para>
+                    <para>実数または複素正方行列, 多項式または有理行列.</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>m</term>
                 <listitem>
-                    <para>real or complex number, the determinant base 10 mantissae</para>
+                    <para>実数または複素数, 行列式の 10 を基底とする仮数</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>e</term>
                 <listitem>
-                    <para>integer, the determinant base 10 exponent</para>
+                    <para>整数, 行列式の 10 を基底とする指数</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>det(X)</literal> ( <literal>m*10^e</literal> is the determinant of the square matrix <literal>X</literal>.
+            <literal>det(X)</literal> ( <literal>m*10^e</literal>は
+            正方行列<literal>X</literal>の行列式である.
         </para>
         <para>
-            For polynomial matrix <literal>det(X)</literal> is equivalent to <literal>determ(X)</literal>.
+            多項式行列 <literal>det(X)</literal> は
+            <literal>determ(X)</literal>に等しい.
         </para>
         <para>
-            For rational matrices <literal>det(X)</literal> is equivalent to <literal>detr(X)</literal>.
+            有理行列の場合, <literal>det(X)</literal> は
+            <literal>detr(X)</literal>に等しい.
         </para>
     </refsection>
     <refsection>
-        <title>References</title>
+        <title>参照</title>
         <para>
-            det computations are based on the Lapack routines
-            DGETRF for  real matrices and  ZGETRF for the complex case.
+            det の計算は Lapack ルーチン DGETRF (実数行列の場合) および
+            ZGETRF (複素数の場合)に基づいている.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 x=poly(0,'x');
 det([x,1+x;2-x,x^2])
-w=ssrand(2,2,4);roots(det(systmat(w))),trzeros(w)   //zeros of linear system
+w=ssrand(2,2,4);roots(det(systmat(w))),trzeros(w)   // 線形システムのゼロ
 A=rand(3,3);
 det(A), prod(spec(A))
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参考</title>
         <simplelist type="inline">
             <member>
                 <link linkend="detr">detr</link>
index e84d0ea..e67efd9 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="orth">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="orth">
     <refnamediv>
         <refname>orth</refname>
-        <refpurpose> orthogonal basis</refpurpose>
+        <refpurpose>直交基底</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>Q=orth(A)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Q</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>Q=orth(A)</literal> returns <literal>Q</literal>, an orthogonal
-            basis for the span of <literal>A</literal>.  Range(<literal>Q</literal>) =
-            Range(<literal>A</literal>) and <literal>Q'*Q=eye</literal>.
+            <literal>Q=orth(A)</literal> は,
+            <literal>A</literal>の範囲での直交基底である
+            <literal>Q</literal>を返します.
+            Range(<literal>Q</literal>) =
+            Range(<literal>A</literal>) および <literal>Q'*Q=eye</literal>.
         </para>
         <para>
-            The number of columns of <literal>Q</literal> is the rank of
-            <literal>A</literal> as determined by the QR algorithm.
+            <literal>Q</literal>の列の数は,
+            QRアルゴリズムで定義された
+            <literal>A</literal>のランクです.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(5,3)*rand(3,4);
 [X,dim]=rowcomp(A);X=X';
 svd([orth(A),X(:,1:dim)])
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="qr">qr</link>
index 4848dd0..e5a4f1c 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="rank">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="rank">
     <refnamediv>
         <refname>rank</refname>
-        <refpurpose> rank</refpurpose>
+        <refpurpose>階数</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[i]=rank(X)
             [i]=rank(X,tol)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>nonnegative real number</para>
+                    <para>非負実数</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>rank(X)</literal> is the numerical rank of <literal>X</literal>
-            i.e. the number of singular values of X that are larger than
-            <literal>norm(size(X),'inf') * norm(X) * %eps</literal>.
+            <literal>rank(X)</literal> は, <literal>X</literal>の数値的な階数(ランク),
+            すなわち <literal>norm(size(X),'inf') * norm(X) * %eps</literal> より大きな
+            X の特異値の数です.
         </para>
         <para>
-            <literal>rank(X,tol)</literal> is the number of singular values of
-            <literal>X</literal> that are larger than <literal>tol</literal>.
+            <literal>rank(X,tol)</literal> は,<literal>tol</literal>
+            より大きな<literal>X</literal>の特異値の数です.
         </para>
         <para>
-            Note that the default value of <literal>tol</literal> is proportional to
-            <literal>norm(X)</literal>. As a consequence
-            <literal>rank([1.d-80,0;0,1.d-80])</literal> is 2 !.
+            <literal>tol</literal> のデフォルト値は
+            <literal>norm(X)</literal>に比例することに注意してください. 
+            結果として,<literal>rank([1.d-80,0;0,1.d-80])</literal> は 2 になります!.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 rank([1.d-80,0;0,1.d-80])
 rank([1,0;0,1.d-80])
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="svd">svd</link>
index f6a1972..0bd1eb2 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="rcond">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="rcond">
     <refnamediv>
         <refname>rcond</refname>
-        <refpurpose>  inverse condition number</refpurpose>
+        <refpurpose>条件数の逆数</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>rcond(X)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>real or complex square matrix</para>
+                    <para>実数または複素数の正方行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>rcond(X)</literal> is an estimate for the reciprocal of the
-            condition of <literal>X</literal> in the 1-norm.
+            <literal>rcond(X)</literal> は,1-ノルムにおける
+            <literal>X</literal>の条件の逆数の推定値です.
         </para>
         <para>
-            If <literal>X</literal> is well conditioned, <literal>rcond(X)</literal> is close to 1.
-            If not, <literal>rcond(X)</literal> is close to 0.
+            <literal>X</literal>が健全な場合,
+            <literal>rcond(X)</literal> は 1 に近くなります.
+            そうでない場合, <literal>rcond(X)</literal> は 0に近くなります.
         </para>
         <para>
-            We compute the 1-norm of A with Lapack/DLANGE, compute its LU decomposition with Lapack/DGETRF 
-            and finally estimate the condition with Lapack/DGECON.
+            <literal>[r,z]=rcond(X)</literal> は
+            <literal>r</literal>に<literal>rcond(X)</literal>を設定し,
+            <literal>norm(X*z,1) = r*norm(X,1)*norm(z,1)</literal>となるような
+            <literal>z</literal>を返します.
+        </para>
+        <para>
+            つまり, <literal>rcond</literal> が小さい場合,
+            <literal>z</literal> はカーネルのベクトルとなります.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=diag([1:10]);
 rcond(A)
 A(1,1)=0.000001;
 rcond(A)
  ]]></programlisting>
-        <para>
-            Estimating the 1-norm inverse condition number with <literal>rcond</literal> is 
-            much faster than computing the 2-norm condition number with <literal>cond</literal>.
-            As a trade-off, <literal>rcond</literal> may be less reliable.
-        </para>
-        <programlisting role="example"><![CDATA[ 
-    A=ones(1000,1000);
-    timer();cond(A);timer()
-    timer();1/rcond(A);timer()
- ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="svd">svd</link>
index be61952..282ed4d 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="rref">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="rref">
     <refnamediv>
         <refname>rref</refname>
-        <refpurpose> computes  matrix row echelon form by lu transformations</refpurpose>
+        <refpurpose> LU分解により行echelon形式の行列を計算</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>R=rref(A)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para> m x n matrix with scalar entries</para>
+                    <para> スカラーのエントリを有するm x n 行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>R</term>
                 <listitem>
-                    <para> m x n matrix,row echelon form of a</para>
+                    <para> Aの行echelon形式のm x n行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>rref</literal> computes the row echelon form of the given matrix by left lu
-            decomposition. If ones need the transformation used just call
-            <literal>X=rref([A,eye(m,m)])</literal> the row echelon form <literal>R</literal> is <literal>X(:,1:n)</literal> and
-            the left transformation <literal>L</literal> is given by <literal>X(:,n+1:n+m)</literal> such as <literal>L*A=R</literal>
+            <literal>rref</literal> は左LU分解により指定した行列
+            の行echelon形式を計算します.
+            <literal>X=rref([A,eye(m,m)])</literal>をコールする際に使用した
+            変換が必要な場合,行echelon形式は<literal>X(:,1:n)</literal>となり,
+            左分解<literal>L</literal>は<literal>L*A=R</literal>となるような
+            <literal>X(:,n+1:n+m)</literal> により指定されます.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=[1 2;3 4;5 6];
 X=rref([A,eye(3,3)]);
@@ -54,8 +56,8 @@ R=X(:,1:2)
 L=X(:,3:5);L*A
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="lu">lu</link>
index 56af8a0..eab122f 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="trace">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="trace">
     <refnamediv>
         <refname>trace</refname>
-        <refpurpose> trace</refpurpose>
+        <refpurpose>トレース</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>trace(X)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>real or complex square matrix, polynomial or rational matrix.</para>
+                    <para>実数または複素行列, 多項式または有理行列.</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>trace(X)</literal> is the trace of the matrix <literal>X</literal>.
+            <literal>trace(X)</literal>は行列<literal>X</literal>の
+            トレースとなる.
         </para>
         <para>
-            Same as <literal>sum(diag(X))</literal>.
+            <literal>sum(diag(X))</literal>と同じである.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(3,3);
 trace(A)-sum(spec(A))
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参考</title>
         <simplelist type="inline">
             <member>
                 <link linkend="det">det</link>
index b4c281f..83783f1 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="expm">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="expm">
     <refnamediv>
         <refname>expm</refname>
-        <refpurpose> square matrix exponential</refpurpose>
+        <refpurpose> 正方行列の指数関数</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>expm(X)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>square matrix with real or complex entries.</para>
+                    <para>実数または複素数のエントリを有する正方行列.</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>X</literal> is a square matrix <literal>expm(X)</literal> is the matrix
+            <literal>X</literal> が正方行列の時,
+            <literal>expm(X)</literal> は以下の行列となります
         </para>
         <para>
             <literal>expm(X) = I + X + X^2 /2 + ...</literal>
         </para>
         <para>
-            The computation is performed by first 
-            block-diagonalizing <literal>X</literal> and then applying a Pade approximation 
-            on each block.
+            計算はまず<literal>X</literal>をブロック対角化した後,
+            各ブロックにパデ近似を適用します.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 X=[1 2;3 4]
 expm(X)
 logm(expm(X))    
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="logm">logm</link>
index 2baa2ce..8a61bed 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="polar">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="polar">
     <refnamediv>
         <refname>polar</refname>
-        <refpurpose> polar form</refpurpose>
+        <refpurpose>極座標形式</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[Ro,Theta]=polar(A)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>real or complex square matrix</para>
+                    <para>実数または複素数の正方行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Ro,  </term>
                 <listitem>
-                    <para>real matrix</para>
+                    <para>実数行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Theta,  </term>
                 <listitem>
-                    <para>real or complex matrix</para>
+                    <para>実数または複素数の行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            <literal>[Ro,Theta]=polar(A)</literal> returns the polar form of
-            <literal>A</literal> i.e.  <literal>A=Ro*expm(%i*Theta)</literal><literal>Ro</literal> symmetric &gt;=0 and <literal>Theta</literal> hermitian
-            &gt;=0.
+            <literal>[Ro,Theta]=polar(A)</literal> は
+            <literal>A</literal>の極座標形式,すなわち,
+            <literal>A=Ro*expm(%i*Theta)</literal>,
+            対称行列 <literal>Ro</literal> &gt;=0
+            およびエルミート行列 <literal>Theta</literal> &gt;=0 を返します.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 A=rand(5,5);
 [Ro,Theta]=polar(A);
 norm(A-Ro*expm(%i*Theta),1)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="expm">expm</link>
@@ -69,4 +71,8 @@ norm(A-Ro*expm(%i*Theta),1)
             </member>
         </simplelist>
     </refsection>
+    <refsection>
+        <title>作者</title>
+        <para>F. Delebecque INRIA; ;   </para>
+    </refsection>
 </refentry>
index e03e86b..8c05f0d 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="companion">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="companion">
     <refnamediv>
         <refname>companion</refname>
-        <refpurpose> companion matrix</refpurpose>
+        <refpurpose>コンパニオン行列 </refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>A=companion(p)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>p</term>
                 <listitem>
-                    <para>polynomial or vector of polynomials</para>
+                    <para>多項式または多項式のベクトル</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>square matrix</para>
+                    <para>正方行列</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Returns a matrix <literal>A</literal> with characteristic polynomial equal
-            to <literal>p</literal> if <literal>p</literal> is monic. If <literal>p</literal> is not monic
-            the characteristic polynomial of <literal>A</literal> is equal to
-            <literal>p/c</literal> where <literal>c</literal> is the coefficient of largest degree
-            in <literal>p</literal>.
+            特性多項式を有する
+            行列<literal>A</literal>を返します.
+            <literal>p</literal>がモニックな場合,特性多項式は
+            <literal>p</literal>に等しくなります.
+            <literal>p</literal>がモニックでない場合,
+            <literal>A</literal>の特性方程式は
+            <literal>p/c</literal>に等しくなります.
+            ただし,<literal>c</literal>は<literal>p</literal>
+            の最大次数の係数です.
         </para>
         <para>
-            If <literal>p</literal> is a vector of monic polynomials, <literal>A</literal> is block diagonal,
-            and the characteristic polynomial of the ith block is <literal>p(i)</literal>.
+            <literal>p</literal> がモニックな多項式のベクトルの場合,
+            <literal>A</literal> はブロック対角となり,
+            i番目の特性多項式は
+            <literal>p(i)</literal>となります.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 s=poly(0,'s');
 p=poly([1,2,3,4,1],'s','c')
@@ -60,8 +66,8 @@ roots(p)
 spec(companion(p))
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="spec">spec</link>
@@ -74,4 +80,8 @@ spec(companion(p))
             </member>
         </simplelist>
     </refsection>
+    <refsection>
+        <title>作者</title>
+        <para>F.D.  </para>
+    </refsection>
 </refentry>
index 70d981c..5a8c8f9 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="ereduc">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="ereduc">
     <refnamediv>
         <refname>ereduc</refname>
-        <refpurpose> computes  matrix column echelon form by qz transformations</refpurpose>
+        <refpurpose>qz変換により列階段形行列を計算</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[E,Q,Z [,stair [,rk]]]=ereduc(X,tol)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>X</term>
                 <listitem>
-                    <para>m x n matrix with real  entries.</para>
+                    <para>実数エントリを有するm x n 行列.</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>real positive scalar.</para>
+                    <para>実数の正のスカラー.</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>E</term>
                 <listitem>
-                    <para>column echelon form matrix</para>
+                    <para>列階段形行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Q</term>
                 <listitem>
-                    <para>m x m unitary matrix</para>
+                    <para>m x m ユニタリ行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Z</term>
                 <listitem>
-                    <para>n x n unitary matrix</para>
+                    <para>n x n ユニタリ行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>stair</term>
                 <listitem>
-                    <para>vector of indexes,</para>
+                    <para>添字ベクトル,</para>
                     <variablelist>
                         <varlistentry>
                             <term>*  </term>
                             <listitem>
                                 <para>
-                                    <literal>ISTAIR(i) = + j</literal>  if the boundary element <literal>E(i,j)</literal> is a   corner point.
+                                    境界要素<literal>E(i,j)</literal>がコーナ点の場合,
+                                    <literal>ISTAIR(i) = + j</literal>.
                                 </para>
                             </listitem>
                         </varlistentry>
@@ -69,7 +70,8 @@
                             <term>*  </term>
                             <listitem>
                                 <para>
-                                    <literal>ISTAIR(i) = - j</literal>   if the boundary element <literal>E(i,j)</literal> is not a corner point.
+                                    境界要素<literal>E(i,j)</literal>がコーナ点でない場合,
+                                    <literal>ISTAIR(i) = - j</literal>.
                                 </para>
                             </listitem>
                         </varlistentry>
             <varlistentry>
                 <term>rk</term>
                 <listitem>
-                    <para>integer, estimated rank of the matrix</para>
+                    <para>整数, 行列のランクの推定値</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Given an <literal>m x n</literal> matrix <literal>X</literal> (not necessarily regular) the function 
-            ereduc computes a unitary transformed matrix <literal>E=Q*X*Z</literal> which is in 
-            column echelon form (trapezoidal form). Furthermore the rank of
-            matrix <literal>X</literal> is determined.
+            <literal>m x n</literal>行列<literal>X</literal> (正則である
+            必要はない)を指定すると,
+            関数ereducは,列階段形(台形)の
+            ユニタリ変換行列<literal>E=Q*X*Z</literal>
+            を計算します.
+            更に行列<literal>X</literal>のランクが定義されます.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 X=[1 2 3;4 5 6]
 [E,Q,Z ,stair ,rk]=ereduc(X,1.d-15)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="fstair">fstair</link>
             </member>
         </simplelist>
     </refsection>
+    <refsection>
+        <title>作者</title>
+        <para>Th.G.J. Beelen (Philips Glass Eindhoven). SLICOT</para>
+    </refsection>
 </refentry>
index 670bbde..f103579 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="fstair">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="fstair">
     <refnamediv>
         <refname>fstair</refname>
-        <refpurpose> computes  pencil  column echelon form by qz transformations</refpurpose>
+        <refpurpose>qz変換により列階段形ペンシルを計算する</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[AE,EE,QE,ZE,blcks,muk,nuk,muk0,nuk0,mnei]=fstair(A,E,Q,Z,stair,rk,tol)</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>A</term>
                 <listitem>
-                    <para>m x n matrix with real  entries.</para>
+                    <para>実数エントリを有するm x n行列.</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>tol</term>
                 <listitem>
-                    <para>real positive scalar.</para>
+                    <para>実数の正のスカラー.</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>E</term>
                 <listitem>
-                    <para>column echelon form matrix</para>
+                    <para>列階段形行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Q</term>
                 <listitem>
-                    <para>m x m unitary matrix</para>
+                    <para>m x m ユニタリ行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Z</term>
                 <listitem>
-                    <para>n x n unitary matrix</para>
+                    <para>n x n ユニタリ行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>stair</term>
                 <listitem>
-                    <para>vector of indexes (see ereduc)</para>
+                    <para>添字ベクトル (ereduc参照)</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>rk</term>
                 <listitem>
-                    <para>integer, estimated rank of the matrix</para>
+                    <para>整数, 行列ランクの推定値</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>AE</term>
                 <listitem>
-                    <para>m x n matrix with real  entries.</para>
+                    <para>実数エントリを有するm x n行列.</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>EE</term>
                 <listitem>
-                    <para>column echelon form matrix</para>
+                    <para>列階段形行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>QE</term>
                 <listitem>
-                    <para>m x m unitary matrix</para>
+                    <para>m x m ユニタリ行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>ZE</term>
                 <listitem>
-                    <para>n x n unitary matrix</para>
+                    <para>n x n ユニタリ行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>nblcks</term>
                 <listitem>
                     <para>
-                        is the number of submatrices having full row rank &gt;= 0  detected in matrix  <literal>A</literal>.
+                        行列<literal>A</literal>で検出された
+                        フル行ランクを有するサブ行列の数(&gt;= 0).
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>muk:  </term>
                 <listitem>
-                    <para>integer array of dimension (n). Contains the column dimensions mu(k)  (k=1,...,nblcks) of the submatrices having full column  rank in the pencil sE(eps)-A(eps)</para>
+                    <para>次元 (n) の整数配列.
+                        ペンシルsE(eps)-A(eps)において
+                        列フルランクを有するサブ行列の列次元 mu(k) (k=1,...,nblcks) を含みます.
+                    </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>nuk:  </term>
                 <listitem>
-                    <para>integer array of dimension (m+1). Contains the row dimensions nu(k)  (k=1,...,nblcks) of the submatrices having full row  rank in the pencil sE(eps)-A(eps)</para>
+                    <para>
+                        次元 (m+1) の整数配列.
+                        ペンシルsE(eps)-A(eps)において
+                        行フルランクを有するサブ行列の行次元 nu(k) (k=1,...,nblcks) 
+                        を含みます.
+                    </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>muk0:  </term>
                 <listitem>
-                    <para>integer array of dimension (n). Contains the column dimensions mu(k)  (k=1,...,nblcks) of the submatrices having full column  rank in the pencil sE(eps,inf)-A(eps,inf)</para>
+                    <para>
+                        次元 (n) の整数配列.
+                        ペンシルsE(eps,inf)-A(eps,inf)において
+                        列フルランクを有するサブ行列の列次元 mu(k) (k=1,...,nblcks) を含みます.
+                    </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>nuk:  </term>
                 <listitem>
-                    <para>integer array of dimension (m+1). Contains the row dimensions nu(k)  (k=1,...,nblcks) of the submatrices having full row  rank in the pencil sE(eps,inf)-A(eps,inf)</para>
+                    <para>
+                        次元 (m+1) の整数配列.
+                        ペンシルsE(eps,inf)-A(eps,inf)において
+                        行フルランクを有するサブ行列の行次元 nu(k) (k=1,...,nblcks) 
+                        を含みます.
+                    </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>mnei:  </term>
                 <listitem>
-                    <para>integer array of dimension (4). mnei(1) = row dimension of sE(eps)-A(eps)</para>
+                    <para>次元 (4) の整数配列.
+                        mnei(1) = sE(eps)-A(eps)の行の次元
+                    </para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Given a pencil <literal>sE-A</literal> where matrix <literal>E</literal> is in column echelon form the
-            function  <literal>fstair</literal> computes according to the wishes of the user a
-            unitary transformed pencil <literal>QE(sEE-AE)ZE</literal> which is more or less similar
-            to the generalized Schur form of the pencil <literal>sE-A</literal>.
-            The function  yields also part of the Kronecker structure of
-            the given pencil.
+            行列 <literal>E</literal> を列階段形として,
+            ペンシル <literal>sE-A</literal> を指定すると,
+            関数<literal>fstair</literal>は
+            ユーザの指定に基づき
+            ユニタリ変換されたペンシル<literal>QE(sEE-AE)ZE</literal>を
+            計算します.
+            このペンシルは, ほぼペンシル<literal>sE-A</literal>
+            の一般化Schur形式です.
+            この関数は,指定したペンシルの
+            クロネッカー構造の部分も出力します.
         </para>
         <para>
-            <literal>Q,Z</literal> are the unitary matrices used to compute the pencil where E
-            is in column echelon form (see ereduc)
+            <literal>Q,Z</literal> はユニタリ行列で,
+            ペンシルを計算する際に使用されます.
+            ただし, E は列階段形です (ereduc参照)
         </para>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="quaskro">quaskro</link>
index baa3bdc..b002e09 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="glever">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="glever">
     <refnamediv>
         <refname>glever</refname>
-        <refpurpose> inverse of matrix pencil</refpurpose>
+        <refpurpose>行列ペンシルの逆</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[Bfs,Bis,chis]=glever(E,A [,s])</synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>E, A</term>
                 <listitem>
-                    <para>two real square matrices of same dimensions</para>
+                    <para>同じ次元の正方実行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>s</term>
                 <listitem>
                     <para>
-                        character string (default value '<literal>s</literal>')
+                        文字列 (デフォルト値 '<literal>s</literal>')
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Bfs,Bis</term>
                 <listitem>
-                    <para>two polynomial matrices</para>
+                    <para>多項式行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>chis</term>
                 <listitem>
-                    <para>polynomial</para>
+                    <para>多項式</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
-        <para>
-            Computation of
+        <title>説明</title>
+        <para>一般化したLeverrierのアルゴリズムによりある行列ペンシルについて
         </para>
         <para>
             <literal>(s*E-A)^-1</literal>
         </para>
         <para>
-            by generalized Leverrier's algorithm for a matrix pencil.
+            を計算します.
         </para>
-        <programlisting role=""><![CDATA[ 
+        <programlisting role = ""><![CDATA[ 
 (s*E-A)^-1 = (Bfs/chis) - Bis.
  ]]></programlisting>
         <para>
-            <literal>chis</literal> = characteristic polynomial (up to a multiplicative constant).
+            <literal>chis</literal> = 特性多項式 (乗法定数まで).
         </para>
         <para>
-            <literal>Bfs</literal>  = numerator polynomial matrix.
+            <literal>Bfs</literal>  = 分子の特性多項式行列.
         </para>
         <para>
             <literal>Bis</literal>
-            = polynomial matrix ( - expansion of <literal>(s*E-A)^-1</literal> at infinity).
+            = 多項式行列 ( - <literal>(s*E-A)^-1</literal> の無限大までの級数展開).
         </para>
         <para>
-            Note the - sign before <literal>Bis</literal>.
+            <literal>Bis</literal>の前に - 符号があることに注意してください.
         </para>
     </refsection>
     <refsection>
-        <title>Caution</title>
+        <title>注意</title>
         <para>
-            This function uses <literal>cleanp</literal> to simplify <literal>Bfs,Bis</literal> and <literal>chis</literal>.
+            この関数は,<literal>Bfs,Bis</literal> および <literal>chis</literal>を簡単化するために
+            <literal>cleanp</literal>を使用します.
         </para>
     </refsection>
     <refsection>
-        <title>Examples</title>
+        <title>例</title>
         <programlisting role="example"><![CDATA[ 
 s=%s;F=[-1,s,0,0;0,-1,0,0;0,0,s-2,0;0,0,0,s-1];
 [Bfs,Bis,chis]=glever(F)
 inv(F)-((Bfs/chis) - Bis)
  ]]></programlisting>
     </refsection>
-    <refsection role="see also">
-        <title>See Also</title>
+    <refsection>
+        <title>参照</title>
         <simplelist type="inline">
             <member>
                 <link linkend="rowshuff">rowshuff</link>
index 16aed96..f70ec12 100644 (file)
  * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt
  *
  -->
-<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" version="5.0-subset Scilab" xml:lang="en" xml:id="kroneck">
+<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" version="5.0-subset Scilab" xml:lang="ja" xml:id="kroneck">
     <refnamediv>
         <refname>kroneck</refname>
-        <refpurpose> Kronecker form of matrix pencil</refpurpose>
+        <refpurpose>行列ペンシルのクロネッカー形式</refpurpose>
     </refnamediv>
     <refsynopsisdiv>
-        <title>Calling Sequence</title>
+        <title>呼び出し手順</title>
         <synopsis>[Q,Z,Qd,Zd,numbeps,numbeta]=kroneck(F)
             [Q,Z,Qd,Zd,numbeps,numbeta]=kroneck(E,A)
         </synopsis>
     </refsynopsisdiv>
     <refsection>
-        <title>Arguments</title>
+        <title>パラメータ</title>
         <variablelist>
             <varlistentry>
                 <term>F</term>
                 <listitem>
                     <para>
-                        real matrix pencil <literal>F=s*E-A</literal>
+                        実数行列ペンシル <literal>F=s*E-A</literal>
                     </para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>E,A</term>
                 <listitem>
-                    <para>two real matrices of same dimensions</para>
+                    <para>同じ次元の実数行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Q,Z</term>
                 <listitem>
-                    <para>two square orthogonal matrices</para>
+                    <para>正方直交行列</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>Qd,Zd</term>
                 <listitem>
-                    <para>two vectors of integers</para>
+                    <para>整数ベクトル</para>
                 </listitem>
             </varlistentry>
             <varlistentry>
                 <term>numbeps,numeta</term>
                 <listitem>
-                    <para>two vectors of integers</para>
+                    <para>整数ベクトル</para>
                 </listitem>
             </varlistentry>
         </variablelist>
     </refsection>
     <refsection>
-        <title>Description</title>
+        <title>説明</title>
         <para>
-            Kronecker form of matrix pencil: <literal>kroneck</literal> computes two
-            orthogonal matrices <literal>Q, Z</literal> which put the pencil <literal>F=s*E -A</literal> into
-            upper-triangular form:
+            行列ペンシルのクロネッカー形式: <literal>kroneck</literal> は,
+            ペンシル<literal>F=s*E -A</literal>を以下のような上三角形式に変換する
+            2つの直交行列<literal>Q, Z</literal>を計算します:
         </para>
-        <programlisting role=""><![CDATA[ 
+        <programlisting role = ""><![CDATA[ 
            | sE(eps)-A(eps) |        X       |      X     |      X        |
            |----------------|----------------|------------|---------------|
            |        O       | sE(inf)-A(inf) |      X     |      X        |
@@ -77,47 +77,45 @@ Q(sE-A)Z = |---------------------------------|----------------------------|
            |        0       |       0        |      0     | sE(eta)-A(eta)|
  ]]></programlisting>
         <para>
-            The dimensions of the four blocks are given by:
+            4個のブロックの次元は以下のように指定されます:
         </para>
         <para>
             <literal>eps=Qd(1) x Zd(1)</literal>, <literal>inf=Qd(2) x Zd(2)</literal>,
             <literal>f = Qd(3) x Zd(3)</literal>, <literal>eta=Qd(4)xZd(4)</literal>
         </para>
         <para>
-            The <literal>inf</literal> block contains the infinite modes of
-            the pencil.
+            <literal>inf</literal>ブロックにはペンシルの無限大モードが含まれます.
         </para>
         <para>
-            The <literal>f</literal> block contains the finite modes of
-            the pencil
+            <literal>f</literal> ブロックにはペンシルの有限モードが含まれます.
         </para>
         <para>
-            The structure of epsilon and eta blocks are given by:
+            イプシロンとetaブロックの構造は以下のように指定されます:
         </para>
         <para>
-            <literal>numbep