Scilab Home page | Wiki | Bug tracker | Forge | Mailing list archives | ATOMS | File exchange
Please login or create an account
Change language to: English - Français - Português -

Please note that the recommended version of Scilab is 6.0.1. This page might be outdated.
See the recommended documentation of this function

Scilab help >> Signal Processing > hank

hank

共分散からハンケル行列を得る

呼び出し手順

[hk]=hank(m,n,cov)

パラメータ

m

ブロック行の数

n

ブロック列の数

cov

共分散の系列; 次のように指定します :[R0 R1 R2...Rk]

hk

ハンケル行列の計算値

説明

この関数は,ベクトル過程の共分散系列から 大きさ(m*d,n*d)のハンケル行列を構築します.

//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);

参照

作者

G. Le Vey

Scilab Enterprises
Copyright (c) 2011-2017 (Scilab Enterprises)
Copyright (c) 1989-2012 (INRIA)
Copyright (c) 1989-2007 (ENPC)
with contributors
Last updated:
Thu Mar 03 11:00:55 CET 2011