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annotate m-toolbox/html_help/help/ug/sigproc_example_matrix_linfitsvd_ssm.html @ 8:2f5c9bd7d95d database-connection-manager

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Clarify ltpda_uo.retrieve parameters handling
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 - ssm system model in time 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_linfitsvd.html"><img src="b_prev.gif" border="0" align=
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30 "bottom" alt="Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain"></a>&nbsp;&nbsp;&nbsp;<a href=
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31 "zdomainfit.html"><img src="b_next.gif" border="0" align=
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32 "bottom" alt="Z-Domain Fit"></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 - ssm system model in time 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 - ssm system model in time domain.</p>
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42
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43 <h2>Contents</h2>
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44 <div>
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45 <ul>
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46 <li><a href="#1">set plist for retriving</a></li>
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47 <li><a href="#2">retrive data</a></li>
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48 <li><a href="#3">Load input signal</a></li>
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49 <li><a href="#4">load Whitening filters</a></li>
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50 <li><a href="#5">System Model</a></li>
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51 <li><a href="#6">Build input objects</a></li>
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52 <li><a href="#7">Do Fit</a></li>
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53 </ul>
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54 </div>
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55
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56 <h2>set plist for retriving<a name="1"></a></h2>
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57
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58 <div class="fragment"><pre>
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59
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60 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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61 </pre></div>
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62
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63 <h2>retrive data<a name="2"></a></h2>
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64
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65 <div class="fragment"><pre>
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66
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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>, 68));
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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>, 69));
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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>, 74));
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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>, 75));
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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
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78 is1 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 78));
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79 is2 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 79));
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80
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81 is1ao = is1.getObjectAtIndex(1);
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82 is2ao = is2.getObjectAtIndex(2);
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83
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84 <span class="comment">% set port names for fit</span>
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85 is1names = {<span class="string">'INPUTGUIDANCE.ifo_x1'</span>};
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86 is2names = {<span class="string">'INPUTGUIDANCE.ifo_x12'</span>};
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87
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88 InputNames = {is1names,is2names};
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89 </pre></div>
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90
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91 <h2>load Whitening filters<a name="4"></a></h2>
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92
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93 <div class="fragment"><pre>
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94
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95 <span class="comment">% Stoc filter</span>
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96 fil1 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 76));
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97 fil2 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 77));
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98 fil3 = filterbank(miir());
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99 <span class="comment">% build matrix</span>
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100 wf = matrix(fil1,fil3,fil3,fil2,plist(<span class="string">'shape'</span>,[2 2]));
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101 </pre></div>
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102
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103 <h2>System Model<a name="5"></a></h2>
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104
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105 <div class="fragment"><pre>
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106
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107 H = ssm(plist(<span class="string">'built-in'</span>,<span class="string">'LTP'</span>,<span class="keyword">...</span>
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108 <span class="string">'Version'</span>,<span class="string">'Fitting'</span>,<span class="keyword">...</span>
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109 <span class="string">'Continuous'</span>,true,<span class="keyword">...</span>
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110 <span class="string">'dim'</span>,1,<span class="keyword">...</span>
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111 <span class="string">'SYMBOLIC PARAMS'</span>,<span class="keyword">...</span>
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112 {<span class="string">'FEEPS_XX'</span>,<span class="string">'CAPACT_TM2_XX'</span>,<span class="string">'IFO_X12X1'</span>,<span class="string">'EOM_TM1_STIFF_XX'</span>,<span class="string">'EOM_TM2_STIFF_XX'</span>,<span class="string">'DELAY_X1'</span>,<span class="string">'DELAY_X12'</span>}));
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113 </pre></div>
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114
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115 <h2>Build input objects<a name="6"></a></h2>
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116
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117 <div class="fragment"><pre>
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118
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119 <span class="comment">% empty ao</span>
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120
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121 </pre></div>
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122
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123 <div class="fragment"><pre>
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124
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125 <span class="comment">%%% exp_3_1 %%%</span>
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126 os1 = matrix(o1_1,o12_1,plist(<span class="string">'shape'</span>,[2 1]));
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127
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128 <span class="comment">%%% exp_3_2 %%%</span>
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129 os2 = matrix(o1_2,o12_2,plist(<span class="string">'shape'</span>,[2 1]));
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130
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131 <span class="comment">%%% output names</span>
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132 OutputNames = {{<span class="string">'IFO.x1'</span>,<span class="string">'IFO.x12'</span>},{<span class="string">'IFO.x1'</span>,<span class="string">'IFO.x12'</span>}};
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133
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134 <span class="comment">%%% Input signals</span>
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135 iS = collection(is1ao,is2ao);
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136
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137 <span class="comment">%%% Fit Params %%%</span>
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138 usedparams = {<span class="string">'FEEPS_XX'</span>,<span class="string">'CAPACT_TM2_XX'</span>,<span class="string">'IFO_X12X1'</span>,<span class="string">'EOM_TM1_STIFF_XX'</span>,<span class="string">'EOM_TM2_STIFF_XX'</span>,<span class="string">'DELAY_X1'</span>,<span class="string">'DELAY_X12'</span>};
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139
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140 <span class="comment">%%% set bounded params</span>
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141 bdparams = {<span class="string">'DELAY_X1'</span>,<span class="string">'DELAY_X12'</span>};
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142 bdvals = {[0.1 0.3],[0.1 0.3]};
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143
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144 <span class="comment">%%% set numerical derivative step</span>
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145 diffStep = [0.01,0.01,1e-7,1e-7,1e-7,0.001,0.001];
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146
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147 </pre></div>
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148
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149 <h2>Do Fit<a name="7"></a></h2>
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150
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151 <div class="fragment"><pre>
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152
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153 plfit = plist(<span class="keyword">...</span>
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154 <span class="string">'FitParams'</span>,usedparams,<span class="keyword">...</span>
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155 <span class="string">'BoundedParams'</span>,bdparams,<span class="keyword">...</span>
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156 <span class="string">'BoundVals'</span>,bdvals,<span class="keyword">...</span>
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157 <span class="string">'diffStep'</span>,diffStep,<span class="keyword">...</span>
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158 <span class="string">'Model'</span>,H,<span class="keyword">...</span>
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159 <span class="string">'Input'</span>,iS,<span class="keyword">...</span>
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160 <span class="string">'InputNames'</span>,InputNames,<span class="keyword">...</span>
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161 <span class="string">'OutputNames'</span>,OutputNames,<span class="keyword">...</span>
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162 <span class="string">'WhiteningFilter'</span>,wf,<span class="keyword">...</span>
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163 <span class="string">'tol'</span>,1,<span class="keyword">...</span>
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164 <span class="string">'Nloops'</span>,5,<span class="keyword">...</span>
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165 <span class="string">'Ncut'</span>,1e5);
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166
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167 opars = linfitsvd(os1,os2,plfit);
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168
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169 </pre></div>
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170
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171
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172 </p>
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173
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174 <br>
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175 <br>
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176 <table class="nav" summary="Navigation aid" border="0" width=
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177 "100%" cellpadding="0" cellspacing="0">
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178 <tr valign="top">
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179 <td align="left" width="20"><a href="sigproc_example_matrix_linfitsvd.html"><img src=
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180 "b_prev.gif" border="0" align="bottom" alt=
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181 "Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain"></a>&nbsp;</td>
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182
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183 <td align="left">Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain</td>
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184
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185 <td>&nbsp;</td>
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186
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187 <td align="right">Z-Domain Fit</td>
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188
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189 <td align="right" width="20"><a href=
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190 "zdomainfit.html"><img src="b_next.gif" border="0" align=
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191 "bottom" alt="Z-Domain Fit"></a></td>
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192 </tr>
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193 </table><br>
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194
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195 <p class="copy">&copy;LTP Team</p>
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196 </body>
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197 </html>