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Справка Scilab >> Signal Processing > Correlation Convolution > hank

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 — Тёплицева матрица
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Last updated:
Tue Feb 14 15:13:23 CET 2017