Scilab 5.3.3
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Please note that the recommended version of Scilab is 2025.0.0. This page might be outdated.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);
See Also
- toeplitz — toeplitz matrix
Authors
G. Le Vey
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