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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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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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26 <td valign="baseline"><b>LTPDA Toolbox</b></td><td><a href="../helptoc.html">contents</a></td>
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28 <td valign="baseline" align="right"><a href=
29 "sigproc_example_matrix_linfitsvd.html"><img src="b_prev.gif" border="0" align=
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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32 "bottom" alt="Z-Domain Fit"></a></td>
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35
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>
37 <hr>
38
39 <p>
40
41 <p>Iterative linear parameter estimation for multichannel systems - ssm system model in time domain.</p>
42
43 <h2>Contents</h2>
44 <div>
45 <ul>
46 <li><a href="#1">set plist for retriving</a></li>
47 <li><a href="#2">retrive data</a></li>
48 <li><a href="#3">Load input signal</a></li>
49 <li><a href="#4">load Whitening filters</a></li>
50 <li><a href="#5">System Model</a></li>
51 <li><a href="#6">Build input objects</a></li>
52 <li><a href="#7">Do Fit</a></li>
53 </ul>
54 </div>
55
56 <h2>set plist for retriving<a name="1"></a></h2>
57
58 <div class="fragment"><pre>
59
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>);
61 </pre></div>
62
63 <h2>retrive data<a name="2"></a></h2>
64
65 <div class="fragment"><pre>
66
67 o1_1 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 68));
68 o12_1 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 69));
69
70 o1_2 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 74));
71 o12_2 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 75));
72 </pre></div>
73
74 <h2>Load input signal<a name="3"></a></h2>
75
76 <div class="fragment"><pre>
77
78 is1 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 78));
79 is2 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 79));
80
81 is1ao = is1.getObjectAtIndex(1);
82 is2ao = is2.getObjectAtIndex(2);
83
84 <span class="comment">% set port names for fit</span>
85 is1names = {<span class="string">'INPUTGUIDANCE.ifo_x1'</span>};
86 is2names = {<span class="string">'INPUTGUIDANCE.ifo_x12'</span>};
87
88 InputNames = {is1names,is2names};
89 </pre></div>
90
91 <h2>load Whitening filters<a name="4"></a></h2>
92
93 <div class="fragment"><pre>
94
95 <span class="comment">% Stoc filter</span>
96 fil1 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 76));
97 fil2 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 77));
98 fil3 = filterbank(miir());
99 <span class="comment">% build matrix</span>
100 wf = matrix(fil1,fil3,fil3,fil2,plist(<span class="string">'shape'</span>,[2 2]));
101 </pre></div>
102
103 <h2>System Model<a name="5"></a></h2>
104
105 <div class="fragment"><pre>
106
107 H = ssm(plist(<span class="string">'built-in'</span>,<span class="string">'LTP'</span>,<span class="keyword">...</span>
108 <span class="string">'Version'</span>,<span class="string">'Fitting'</span>,<span class="keyword">...</span>
109 <span class="string">'Continuous'</span>,true,<span class="keyword">...</span>
110 <span class="string">'dim'</span>,1,<span class="keyword">...</span>
111 <span class="string">'SYMBOLIC PARAMS'</span>,<span class="keyword">...</span>
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>}));
113 </pre></div>
114
115 <h2>Build input objects<a name="6"></a></h2>
116
117 <div class="fragment"><pre>
118
119 <span class="comment">% empty ao</span>
120
121 </pre></div>
122
123 <div class="fragment"><pre>
124
125 <span class="comment">%%% exp_3_1 %%%</span>
126 os1 = matrix(o1_1,o12_1,plist(<span class="string">'shape'</span>,[2 1]));
127
128 <span class="comment">%%% exp_3_2 %%%</span>
129 os2 = matrix(o1_2,o12_2,plist(<span class="string">'shape'</span>,[2 1]));
130
131 <span class="comment">%%% output names</span>
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>}};
133
134 <span class="comment">%%% Input signals</span>
135 iS = collection(is1ao,is2ao);
136
137 <span class="comment">%%% Fit Params %%%</span>
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>};
139
140 <span class="comment">%%% set bounded params</span>
141 bdparams = {<span class="string">'DELAY_X1'</span>,<span class="string">'DELAY_X12'</span>};
142 bdvals = {[0.1 0.3],[0.1 0.3]};
143
144 <span class="comment">%%% set numerical derivative step</span>
145 diffStep = [0.01,0.01,1e-7,1e-7,1e-7,0.001,0.001];
146
147 </pre></div>
148
149 <h2>Do Fit<a name="7"></a></h2>
150
151 <div class="fragment"><pre>
152
153 plfit = plist(<span class="keyword">...</span>
154 <span class="string">'FitParams'</span>,usedparams,<span class="keyword">...</span>
155 <span class="string">'BoundedParams'</span>,bdparams,<span class="keyword">...</span>
156 <span class="string">'BoundVals'</span>,bdvals,<span class="keyword">...</span>
157 <span class="string">'diffStep'</span>,diffStep,<span class="keyword">...</span>
158 <span class="string">'Model'</span>,H,<span class="keyword">...</span>
159 <span class="string">'Input'</span>,iS,<span class="keyword">...</span>
160 <span class="string">'InputNames'</span>,InputNames,<span class="keyword">...</span>
161 <span class="string">'OutputNames'</span>,OutputNames,<span class="keyword">...</span>
162 <span class="string">'WhiteningFilter'</span>,wf,<span class="keyword">...</span>
163 <span class="string">'tol'</span>,1,<span class="keyword">...</span>
164 <span class="string">'Nloops'</span>,5,<span class="keyword">...</span>
165 <span class="string">'Ncut'</span>,1e5);
166
167 opars = linfitsvd(os1,os2,plfit);
168
169 </pre></div>
170
171
172 </p>
173
174 <br>
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178 <tr valign="top">
179 <td align="left" width="20"><a href="sigproc_example_matrix_linfitsvd.html"><img src=
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181 "Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain"></a>&nbsp;</td>
182
183 <td align="left">Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain</td>
184
185 <td>&nbsp;</td>
186
187 <td align="right">Z-Domain Fit</td>
188
189 <td align="right" width="20"><a href=
190 "zdomainfit.html"><img src="b_next.gif" border="0" align=
191 "bottom" alt="Z-Domain Fit"></a></td>
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194
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