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Update ltpda_uo.update
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
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1 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
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2 "http://www.w3.org/TR/1999/REC-html401-19991224/loose.dtd">
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3
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4 <html lang="en">
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5 <head>
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6 <meta name="generator" content=
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7 "HTML Tidy for Mac OS X (vers 1st December 2004), see www.w3.org">
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8 <meta http-equiv="Content-Type" content=
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9 "text/html; charset=us-ascii">
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10
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11 <title>Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain (LTPDA Toolbox)</title>
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12 <link rel="stylesheet" href="docstyle.css" type="text/css">
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13 <meta name="generator" content="DocBook XSL Stylesheets V1.52.2">
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14 <meta name="description" content=
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15 "Presents an overview of the features, system requirements, and starting the toolbox.">
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16 </head>
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17
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18 <body>
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19 <a name="top_of_page" id="top_of_page"></a>
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20
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21 <p style="font-size:1px;">&nbsp;</p>
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22
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23 <table class="nav" summary="Navigation aid" border="0" width=
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24 "100%" cellpadding="0" cellspacing="0">
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25 <tr>
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26 <td valign="baseline"><b>LTPDA Toolbox</b></td><td><a href="../helptoc.html">contents</a></td>
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27
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28 <td valign="baseline" align="right"><a href=
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29 "sigproc_example_matrix_linlsqsvd.html"><img src="b_prev.gif" border="0" align=
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30 "bottom" alt="Linear least squares with singular value deconposition - multiple experiments"></a>&nbsp;&nbsp;&nbsp;<a href=
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31 "sigproc_example_matrix_linfitsvd_ssm.html"><img src="b_next.gif" border="0" align=
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32 "bottom" alt="Iterative linear parameter estimation for multichannel systems - ssm system model in time domain"></a></td>
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33 </tr>
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34 </table>
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35
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36 <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>
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37 <hr>
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38
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39 <p>
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40
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41 <p>Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain.</p>
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42
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43 <h2>Contents</h2>
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44 <ul>
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45 <li><a href="#1">set plist for retriving</a></li>
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46 <li><a href="#2">retrive data</a></li>
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47 <li><a href="#3">Load input signal</a></li>
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48 <li><a href="#4">load Whitening filters</a></li>
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49 <li><a href="#6">Build input objects</a></li>
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50 <li><a href="#7">system model 1</a></li>
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51 <li><a href="#8">Do Fit</a></li>
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52 <li><a href="#9">system model 2</a></li>
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53 <li><a href="#10">Set Model Alias</a></li>
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54 <li><a href="#11">Do fit with alias</a></li>
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55 </ul>
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56
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57 <h2>set plist for retriving<a name="1"></a></h2>
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58
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59 <div class="fragment"><pre>
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60
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61 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>);
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62 </pre></div>
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63
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64 <h2>retrive data<a name="2"></a></h2>
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65
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66 <div class="fragment"><pre>
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67 o1_1 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 169));
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68 o12_1 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 170));
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69
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70 o1_2 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 171));
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71 o12_2 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 172));
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72 </pre></div>
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73
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74 <h2>Load input signal<a name="3"></a></h2>
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75
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76 <div class="fragment"><pre>
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77 is1 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 173));
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78 is2 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 180));
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79 </pre></div>
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80
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81 <h2>load Whitening filters<a name="4"></a></h2>
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82 <span class="comment">% Stoc filter</span>
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83
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84 <div class="fragment"><pre>
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85 fil1 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 191));
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86 fil2 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 192));
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87 fil3 = filterbank(miir());
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88 <span class="comment">% build matrix</span>
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89 wf = matrix(fil1,fil3,fil3,fil2,plist(<span class="string">'shape'</span>,[2 2]));
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90 </pre></div>
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91
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92 <h2>Build input objects<a name="6"></a></h2>
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93
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94 <div class="fragment"><pre>
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95
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96 <span class="comment">% empty ao</span>
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97 eao = ao();
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98
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99 <span class="comment">% exp_3_1</span>
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100 os1 = matrix(o1_1,o12_1,plist(<span class="string">'shape'</span>,[2 1]));
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101
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102 <span class="comment">% exp_3_2</span>
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103 os2 = matrix(o1_2,o12_2,plist(<span class="string">'shape'</span>,[2 1]));
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104
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105 <span class="comment">% Input signals</span>
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106 iS = collection(is1,is2);
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107
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108 <span class="comment">% Fit Params</span>
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109 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>};
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110
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111 nsecs = os1.objs(1).data.nsecs;
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112 fs = os1.objs(1).data.fs;
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113 npad = nsecs*fs;
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114
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115 <span class="comment">% set bounded params</span>
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116 bdparams = {<span class="string">'del1'</span>,<span class="string">'del2'</span>};
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117 bdvals = {[0.1 0.3],[0.1 0.3]};
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118
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119 </pre></div>
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120
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121 <h2>system model 1<a name="7"></a></h2>
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122
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123 <div class="fragment"><pre>
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124
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125 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>));
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126 </pre></div>
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127
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128 <h2>Do Fit<a name="8"></a></h2>
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129
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130 <div class="fragment"><pre>
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131
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132 plfit = plist(<span class="keyword">...</span>
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133 <span class="string">'FitParams'</span>,usedparams,<span class="keyword">...</span>
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134 <span class="string">'Model'</span>,H,<span class="keyword">...</span>
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135 <span class="string">'Input'</span>,iS,<span class="keyword">...</span>
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136 <span class="string">'WhiteningFilter'</span>,wf,<span class="keyword">...</span>
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137 <span class="string">'tol'</span>,1,<span class="keyword">...</span>
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138 <span class="string">'Nloops'</span>,10,<span class="keyword">...</span>
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139 <span class="string">'Npad'</span>,npad,<span class="keyword">...</span>
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140 <span class="string">'Ncut'</span>,1e4);
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141
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142 opars1 = linfitsvd(os1,os2,plfit);
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143 </pre></div>
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144
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145 <h2>system model 2<a name="9"></a></h2>
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146
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147 <div class="fragment"><pre>
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148
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149 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>));
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150 </pre></div>
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151
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152 <h2>Set Model Alias<a name="10"></a></h2>
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153
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154 <div class="fragment"><pre>
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155
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156 plalias = plist(<span class="string">'nsecs'</span>,nsecs,<span class="string">'npad'</span>,npad,<span class="string">'fs'</span>,fs);
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157 <span class="keyword">for</span> ii=1:numel(H2.objs)
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158 H2.objs(ii).assignalias(H2.objs(ii),plalias);
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159 <span class="keyword">end</span>
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160 </pre></div>
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161
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162 <h2>Do fit with alias<a name="11"></a></h2>
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163
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164 <div class="fragment"><pre>
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165
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166 plfit2 = plist(<span class="keyword">...</span>
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167 <span class="string">'FitParams'</span>,usedparams,<span class="keyword">...</span>
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168 <span class="string">'Model'</span>,H2,<span class="keyword">...</span>
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169 <span class="string">'BoundedParams'</span>,bdparams,<span class="keyword">...</span>
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170 <span class="string">'BoundVals'</span>,bdvals,<span class="keyword">...</span>
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171 <span class="string">'Input'</span>,iS,<span class="keyword">...</span>
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172 <span class="string">'WhiteningFilter'</span>,wf,<span class="keyword">...</span>
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173 <span class="string">'tol'</span>,1,<span class="keyword">...</span>
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174 <span class="string">'Nloops'</span>,10,<span class="keyword">...</span><span class="comment"> % maximum number of fit iterations</span>
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175 <span class="string">'Npad'</span>,npad,<span class="keyword">...</span>
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176 <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>
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177
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178 opars2 = linfitsvd(os1,os2,plfit2);
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179 </pre></div>
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180
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181
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182 </p>
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183
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184 <br>
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185 <br>
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186 <table class="nav" summary="Navigation aid" border="0" width=
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187 "100%" cellpadding="0" cellspacing="0">
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188 <tr valign="top">
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189 <td align="left" width="20"><a href="sigproc_example_matrix_linlsqsvd.html"><img src=
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190 "b_prev.gif" border="0" align="bottom" alt=
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191 "Linear least squares with singular value deconposition - multiple experiments"></a>&nbsp;</td>
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192
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193 <td align="left">Linear least squares with singular value deconposition - multiple experiments</td>
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194
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195 <td>&nbsp;</td>
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196
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197 <td align="right">Iterative linear parameter estimation for multichannel systems - ssm system model in time domain</td>
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198
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199 <td align="right" width="20"><a href=
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200 "sigproc_example_matrix_linfitsvd_ssm.html"><img src="b_next.gif" border="0" align=
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201 "bottom" alt="Iterative linear parameter estimation for multichannel systems - ssm system model in time domain"></a></td>
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202 </tr>
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203 </table><br>
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204
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Daniele Nicolodi <nicolodi@science.unitn.it>
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205 <p class="copy">&copy;LTP Team</p>
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206 </body>
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207 </html>