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  • Committer: Bazaar Package Importer
  • Author(s): Torsten Werner
  • Date: 2005-01-09 22:58:21 UTC
  • mfrom: (1.1.1 upstream)
  • Revision ID: james.westby@ubuntu.com-20050109225821-473xr8vhgugxxx5j
Tags: 3.0-12
http://bugs.debian.org/255869
changed configure.in to build scilab's own malloc.o, closes: #255869

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man/eng/signal/hank.xml
 
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<?xml version="1.0" encoding="ISO-8859-1" standalone="no"?>
 
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<!DOCTYPE MAN SYSTEM "../../manrev.dtd">
 
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<MAN>
 
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  <LANGUAGE>eng</LANGUAGE>
 
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  <TITLE>hank</TITLE>
 
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  <TYPE>Scilab Function</TYPE>
 
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  <DATE>April 1993</DATE>
 
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  <SHORT_DESCRIPTION name="hank"> covariance to hankel matrix</SHORT_DESCRIPTION>
 
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  <CALLING_SEQUENCE>
 
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    <CALLING_SEQUENCE_ITEM>[hk]=hank(m,n,cov)  </CALLING_SEQUENCE_ITEM>
 
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  </CALLING_SEQUENCE>
 
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  <PARAM>
 
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    <PARAM_INDENT>
 
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      <PARAM_ITEM>
 
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        <PARAM_NAME>m</PARAM_NAME>
 
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        <PARAM_DESCRIPTION>
 
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          <SP>: number of bloc-rows</SP>
 
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        </PARAM_DESCRIPTION>
 
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      </PARAM_ITEM>
 
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      <PARAM_ITEM>
 
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        <PARAM_NAME>n</PARAM_NAME>
 
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        <PARAM_DESCRIPTION>
 
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          <SP>: number of bloc-columns</SP>
 
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        </PARAM_DESCRIPTION>
 
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      </PARAM_ITEM>
 
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      <PARAM_ITEM>
 
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        <PARAM_NAME>cov</PARAM_NAME>
 
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        <PARAM_DESCRIPTION>
 
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          <SP>: sequence of covariances; it must be given as :[R0 R1 R2...Rk]</SP>
 
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        </PARAM_DESCRIPTION>
 
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      </PARAM_ITEM>
 
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      <PARAM_ITEM>
 
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        <PARAM_NAME>hk</PARAM_NAME>
 
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        <PARAM_DESCRIPTION>
 
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          <SP>: computed hankel matrix</SP>
 
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        </PARAM_DESCRIPTION>
 
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      </PARAM_ITEM>
 
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    </PARAM_INDENT>
 
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  </PARAM>
 
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  <DESCRIPTION>
 
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    <P>
 
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    this function builds the hankel matrix of size <VERB>(m*d,n*d)</VERB>
 
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    from the covariance sequence of a vector process</P>
 
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  </DESCRIPTION>
 
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  <EXAMPLE>
 
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<![CDATA[
 
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//Example of how to use the hank macro for 
 
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//building a Hankel matrix from multidimensional 
 
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//data (covariance or Markov parameters e.g.)
 
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//
 
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//This is used e.g. in the solution of normal equations
 
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//by classical identification methods (Instrumental Variables e.g.)
 
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//
 
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//1)let's generate the multidimensional data under the form :
 
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//  C=[c_0 c_1 c_2 .... c_n]
 
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//where each bloc c_k is a d-dimensional matrix (e.g. the k-th correlation 
 
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//of a d-dimensional stochastic process X(t) [c_k = E(X(t) X'(t+k)], ' 
 
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//being the transposition in scilab)
 
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//
 
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//we take here d=2 and n=64
 
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//
 
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c=rand(2,2*64)
 
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//
 
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//generate the hankel matrix H (with 4 bloc-rows and 5 bloc-columns)
 
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//from the data in c
 
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//
 
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H=hank(4,5,c);
 
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//
 
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 ]]>
 
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  </EXAMPLE>
 
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  <SEE_ALSO>
 
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    <SEE_ALSO_ITEM>
 
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      <LINK>toeplitz</LINK>
 
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    </SEE_ALSO_ITEM>
 
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  </SEE_ALSO>
 
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  <AUTHOR>G. Le Vey</AUTHOR>
 
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</MAN>