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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
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1
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2 <p>Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain.</p>
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3
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4 <h2>Contents</h2>
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5 <ul>
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6 <li><a href="#1">set plist for retriving</a></li>
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7 <li><a href="#2">retrive data</a></li>
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8 <li><a href="#3">Load input signal</a></li>
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9 <li><a href="#4">load Whitening filters</a></li>
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10 <li><a href="#6">Build input objects</a></li>
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11 <li><a href="#7">system model 1</a></li>
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12 <li><a href="#8">Do Fit</a></li>
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13 <li><a href="#9">system model 2</a></li>
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14 <li><a href="#10">Set Model Alias</a></li>
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15 <li><a href="#11">Do fit with alias</a></li>
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16 </ul>
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17
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18 <h2>set plist for retriving<a name="1"></a></h2>
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19
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20 <div class="fragment"><pre>
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21
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22 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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23 </pre></div>
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24
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25 <h2>retrive data<a name="2"></a></h2>
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26
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27 <div class="fragment"><pre>
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28 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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29 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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30
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31 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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32 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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33 </pre></div>
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34
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35 <h2>Load input signal<a name="3"></a></h2>
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36
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37 <div class="fragment"><pre>
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38 is1 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 173));
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39 is2 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 180));
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40 </pre></div>
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41
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42 <h2>load Whitening filters<a name="4"></a></h2>
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43 <span class="comment">% Stoc filter</span>
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44
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45 <div class="fragment"><pre>
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46 fil1 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 191));
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47 fil2 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 192));
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48 fil3 = filterbank(miir());
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49 <span class="comment">% build matrix</span>
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50 wf = matrix(fil1,fil3,fil3,fil2,plist(<span class="string">'shape'</span>,[2 2]));
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51 </pre></div>
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52
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53 <h2>Build input objects<a name="6"></a></h2>
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54
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55 <div class="fragment"><pre>
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56
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57 <span class="comment">% empty ao</span>
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58 eao = ao();
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59
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60 <span class="comment">% exp_3_1</span>
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61 os1 = matrix(o1_1,o12_1,plist(<span class="string">'shape'</span>,[2 1]));
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62
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63 <span class="comment">% exp_3_2</span>
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64 os2 = matrix(o1_2,o12_2,plist(<span class="string">'shape'</span>,[2 1]));
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65
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66 <span class="comment">% Input signals</span>
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67 iS = collection(is1,is2);
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68
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69 <span class="comment">% Fit Params</span>
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70 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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71
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72 nsecs = os1.objs(1).data.nsecs;
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73 fs = os1.objs(1).data.fs;
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74 npad = nsecs*fs;
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75
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76 <span class="comment">% set bounded params</span>
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77 bdparams = {<span class="string">'del1'</span>,<span class="string">'del2'</span>};
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78 bdvals = {[0.1 0.3],[0.1 0.3]};
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79
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80 </pre></div>
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81
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82 <h2>system model 1<a name="7"></a></h2>
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83
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84 <div class="fragment"><pre>
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85
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86 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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87 </pre></div>
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88
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89 <h2>Do Fit<a name="8"></a></h2>
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90
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91 <div class="fragment"><pre>
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92
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93 plfit = plist(<span class="keyword">...</span>
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94 <span class="string">'FitParams'</span>,usedparams,<span class="keyword">...</span>
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95 <span class="string">'Model'</span>,H,<span class="keyword">...</span>
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96 <span class="string">'Input'</span>,iS,<span class="keyword">...</span>
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97 <span class="string">'WhiteningFilter'</span>,wf,<span class="keyword">...</span>
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98 <span class="string">'tol'</span>,1,<span class="keyword">...</span>
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99 <span class="string">'Nloops'</span>,10,<span class="keyword">...</span>
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100 <span class="string">'Npad'</span>,npad,<span class="keyword">...</span>
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101 <span class="string">'Ncut'</span>,1e4);
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102
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103 opars1 = linfitsvd(os1,os2,plfit);
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104 </pre></div>
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105
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106 <h2>system model 2<a name="9"></a></h2>
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107
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108 <div class="fragment"><pre>
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109
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110 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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111 </pre></div>
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112
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113 <h2>Set Model Alias<a name="10"></a></h2>
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114
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115 <div class="fragment"><pre>
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116
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117 plalias = plist(<span class="string">'nsecs'</span>,nsecs,<span class="string">'npad'</span>,npad,<span class="string">'fs'</span>,fs);
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118 <span class="keyword">for</span> ii=1:numel(H2.objs)
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119 H2.objs(ii).assignalias(H2.objs(ii),plalias);
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120 <span class="keyword">end</span>
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121 </pre></div>
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122
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123 <h2>Do fit with alias<a name="11"></a></h2>
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124
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125 <div class="fragment"><pre>
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126
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127 plfit2 = plist(<span class="keyword">...</span>
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128 <span class="string">'FitParams'</span>,usedparams,<span class="keyword">...</span>
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129 <span class="string">'Model'</span>,H2,<span class="keyword">...</span>
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130 <span class="string">'BoundedParams'</span>,bdparams,<span class="keyword">...</span>
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131 <span class="string">'BoundVals'</span>,bdvals,<span class="keyword">...</span>
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132 <span class="string">'Input'</span>,iS,<span class="keyword">...</span>
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133 <span class="string">'WhiteningFilter'</span>,wf,<span class="keyword">...</span>
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134 <span class="string">'tol'</span>,1,<span class="keyword">...</span>
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135 <span class="string">'Nloops'</span>,10,<span class="keyword">...</span><span class="comment"> % maximum number of fit iterations</span>
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136 <span class="string">'Npad'</span>,npad,<span class="keyword">...</span>
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137 <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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138
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139 opars2 = linfitsvd(os1,os2,plfit2);
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140 </pre></div>
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141