hank covariance to hankel matrix Syntax hk =hank(m, n, cov) Arguments m number of bloc-rows n number of bloc-columns cov sequence of covariances; it must be given as :[R0 R1 R2...Rk] hk computed hankel matrix Description This function builds the hankel matrix of size (m*d,n*d) from the covariance sequence of a vector process. More precisely: This function builds the hankel matrix of size (m*d,n*d) from the covariance sequence of a vector process. More precisely: Examples //Example of how to use the hank macro for //building a Hankel matrix from multidimensional //data (covariance or Markov parameters e.g.) // //This is used e.g. in the solution of normal equations //by classical identification methods (Instrumental Variables e.g.) // //1)let's generate the multidimensional data under the form : // C=[c_0 c_1 c_2 .... c_n] //where each bloc c_k is a d-dimensional matrix (e.g. the k-th correlation //of a d-dimensional stochastic process X(t) [c_k = E(X(t) X'(t+k)], ' //being the transposition in scilab) // //we take here d=2 and n=64 c = rand(2, 2 * 64) //generate the hankel matrix H (with 4 bloc-rows and 5 bloc-columns) //from the data in c H = hank(4, 5, c); See also toeplitz