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Import.
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Wed, 23 Nov 2011 19:22:13 +0100 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/m-toolbox/html_help/help/ug/sigproc_example_matrix_linfitsvd_content.html Wed Nov 23 19:22:13 2011 +0100 @@ -0,0 +1,141 @@ + +<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> +