Mercurial > hg > ltpda
view m-toolbox/html_help/help/ug/sigproc_example_matrix_linfitsvd.html @ 51:9d5c88356247 database-connection-manager
Make unit tests database connection parameters configurable
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Wed, 07 Dec 2011 17:24:37 +0100 |
parents | f0afece42f48 |
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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/1999/REC-html401-19991224/loose.dtd"> <html lang="en"> <head> <meta name="generator" content= "HTML Tidy for Mac OS X (vers 1st December 2004), see www.w3.org"> <meta http-equiv="Content-Type" content= "text/html; charset=us-ascii"> <title>Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain (LTPDA Toolbox)</title> <link rel="stylesheet" href="docstyle.css" type="text/css"> <meta name="generator" content="DocBook XSL Stylesheets V1.52.2"> <meta name="description" content= "Presents an overview of the features, system requirements, and starting the toolbox."> </head> <body> <a name="top_of_page" id="top_of_page"></a> <p style="font-size:1px;"> </p> <table class="nav" summary="Navigation aid" border="0" width= "100%" cellpadding="0" cellspacing="0"> <tr> <td valign="baseline"><b>LTPDA Toolbox</b></td><td><a href="../helptoc.html">contents</a></td> <td valign="baseline" align="right"><a href= "sigproc_example_matrix_linlsqsvd.html"><img src="b_prev.gif" border="0" align= "bottom" alt="Linear least squares with singular value deconposition - multiple experiments"></a> <a href= "sigproc_example_matrix_linfitsvd_ssm.html"><img src="b_next.gif" border="0" align= "bottom" alt="Iterative linear parameter estimation for multichannel systems - ssm system model in time domain"></a></td> </tr> </table> <h1 class="title"><a name="f3-12899" id="f3-12899"></a>Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain</h1> <hr> <p> <p>Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain.</p> <h2>Contents</h2> <ul> <li><a href="#1">set plist for retriving</a></li> <li><a href="#2">retrive data</a></li> <li><a href="#3">Load input signal</a></li> <li><a href="#4">load Whitening filters</a></li> <li><a href="#6">Build input objects</a></li> <li><a href="#7">system model 1</a></li> <li><a href="#8">Do Fit</a></li> <li><a href="#9">system model 2</a></li> <li><a href="#10">Set Model Alias</a></li> <li><a href="#11">Do fit with alias</a></li> </ul> <h2>set plist for retriving<a name="1"></a></h2> <div class="fragment"><pre> pl = plist(<span class="string">'hostname'</span>, <span class="string">'lpsdas01.esac.esa.int'</span>, <span class="string">'database'</span>, <span class="string">'ex6'</span>); </pre></div> <h2>retrive data<a name="2"></a></h2> <div class="fragment"><pre> o1_1 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 169)); o12_1 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 170)); o1_2 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 171)); o12_2 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 172)); </pre></div> <h2>Load input signal<a name="3"></a></h2> <div class="fragment"><pre> is1 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 173)); is2 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 180)); </pre></div> <h2>load Whitening filters<a name="4"></a></h2> <span class="comment">% Stoc filter</span> <div class="fragment"><pre> fil1 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 191)); fil2 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 192)); fil3 = filterbank(miir()); <span class="comment">% build matrix</span> wf = matrix(fil1,fil3,fil3,fil2,plist(<span class="string">'shape'</span>,[2 2])); </pre></div> <h2>Build input objects<a name="6"></a></h2> <div class="fragment"><pre> <span class="comment">% empty ao</span> eao = ao(); <span class="comment">% exp_3_1</span> os1 = matrix(o1_1,o12_1,plist(<span class="string">'shape'</span>,[2 1])); <span class="comment">% exp_3_2</span> os2 = matrix(o1_2,o12_2,plist(<span class="string">'shape'</span>,[2 1])); <span class="comment">% Input signals</span> iS = collection(is1,is2); <span class="comment">% Fit Params</span> usedparams = {<span class="string">'A1'</span>,<span class="string">'A2'</span>,<span class="string">'S21'</span>,<span class="string">'w1'</span>,<span class="string">'w12'</span>,<span class="string">'del1'</span>,<span class="string">'del2'</span>}; nsecs = os1.objs(1).data.nsecs; fs = os1.objs(1).data.fs; npad = nsecs*fs; <span class="comment">% set bounded params</span> bdparams = {<span class="string">'del1'</span>,<span class="string">'del2'</span>}; bdvals = {[0.1 0.3],[0.1 0.3]}; </pre></div> <h2>system model 1<a name="7"></a></h2> <div class="fragment"><pre> H = matrix(plist(<span class="string">'built-in'</span>,<span class="string">'ifo2ifo'</span>, <span class="string">'Version'</span>, <span class="string">'LSS v4.9.2 Phys Params'</span>)); </pre></div> <h2>Do Fit<a name="8"></a></h2> <div class="fragment"><pre> plfit = plist(<span class="keyword">...</span> <span class="string">'FitParams'</span>,usedparams,<span class="keyword">...</span> <span class="string">'Model'</span>,H,<span class="keyword">...</span> <span class="string">'Input'</span>,iS,<span class="keyword">...</span> <span class="string">'WhiteningFilter'</span>,wf,<span class="keyword">...</span> <span class="string">'tol'</span>,1,<span class="keyword">...</span> <span class="string">'Nloops'</span>,10,<span class="keyword">...</span> <span class="string">'Npad'</span>,npad,<span class="keyword">...</span> <span class="string">'Ncut'</span>,1e4); opars1 = linfitsvd(os1,os2,plfit); </pre></div> <h2>system model 2<a name="9"></a></h2> <div class="fragment"><pre> H2 = matrix(plist(<span class="string">'built-in'</span>,<span class="string">'ifo2ifo'</span>, <span class="string">'Version'</span>, <span class="string">'LSS v4.9.2 Phys Params Alias'</span>)); </pre></div> <h2>Set Model Alias<a name="10"></a></h2> <div class="fragment"><pre> plalias = plist(<span class="string">'nsecs'</span>,nsecs,<span class="string">'npad'</span>,npad,<span class="string">'fs'</span>,fs); <span class="keyword">for</span> ii=1:numel(H2.objs) H2.objs(ii).assignalias(H2.objs(ii),plalias); <span class="keyword">end</span> </pre></div> <h2>Do fit with alias<a name="11"></a></h2> <div class="fragment"><pre> plfit2 = plist(<span class="keyword">...</span> <span class="string">'FitParams'</span>,usedparams,<span class="keyword">...</span> <span class="string">'Model'</span>,H2,<span class="keyword">...</span> <span class="string">'BoundedParams'</span>,bdparams,<span class="keyword">...</span> <span class="string">'BoundVals'</span>,bdvals,<span class="keyword">...</span> <span class="string">'Input'</span>,iS,<span class="keyword">...</span> <span class="string">'WhiteningFilter'</span>,wf,<span class="keyword">...</span> <span class="string">'tol'</span>,1,<span class="keyword">...</span> <span class="string">'Nloops'</span>,10,<span class="keyword">...</span><span class="comment"> % maximum number of fit iterations</span> <span class="string">'Npad'</span>,npad,<span class="keyword">...</span> <span class="string">'Ncut'</span>,1e4); <span class="comment">% number of data points to skip at the starting of the series to avoid whitening filter transient</span> opars2 = linfitsvd(os1,os2,plfit2); </pre></div> </p> <br> <br> <table class="nav" summary="Navigation aid" border="0" width= "100%" cellpadding="0" cellspacing="0"> <tr valign="top"> <td align="left" width="20"><a href="sigproc_example_matrix_linlsqsvd.html"><img src= "b_prev.gif" border="0" align="bottom" alt= "Linear least squares with singular value deconposition - multiple experiments"></a> </td> <td align="left">Linear least squares with singular value deconposition - multiple experiments</td> <td> </td> <td align="right">Iterative linear parameter estimation for multichannel systems - ssm system model in time domain</td> <td align="right" width="20"><a href= "sigproc_example_matrix_linfitsvd_ssm.html"><img src="b_next.gif" border="0" align= "bottom" alt="Iterative linear parameter estimation for multichannel systems - ssm system model in time domain"></a></td> </tr> </table><br> <p class="copy">©LTP Team</p> </body> </html>