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Please note that the recommended version of Scilab is 6.1.0. This page might be outdated.
See the recommended documentation of this function

hank

covariance to hankel matrix

Calling Sequence

`[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

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);```

G. Le Vey

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