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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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1
2 <p>Iterative linear parameter estimation for multichannel systems - symbolic system model in frequency domain.</p>
3
4 <h2>Contents</h2>
5 <ul>
6 <li><a href="#1">set plist for retriving</a></li>
7 <li><a href="#2">retrive data</a></li>
8 <li><a href="#3">Load input signal</a></li>
9 <li><a href="#4">load Whitening filters</a></li>
10 <li><a href="#6">Build input objects</a></li>
11 <li><a href="#7">system model 1</a></li>
12 <li><a href="#8">Do Fit</a></li>
13 <li><a href="#9">system model 2</a></li>
14 <li><a href="#10">Set Model Alias</a></li>
15 <li><a href="#11">Do fit with alias</a></li>
16 </ul>
17
18 <h2>set plist for retriving<a name="1"></a></h2>
19
20 <div class="fragment"><pre>
21
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>);
23 </pre></div>
24
25 <h2>retrive data<a name="2"></a></h2>
26
27 <div class="fragment"><pre>
28 o1_1 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 169));
29 o12_1 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 170));
30
31 o1_2 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 171));
32 o12_2 = ao(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 172));
33 </pre></div>
34
35 <h2>Load input signal<a name="3"></a></h2>
36
37 <div class="fragment"><pre>
38 is1 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 173));
39 is2 = matrix(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 180));
40 </pre></div>
41
42 <h2>load Whitening filters<a name="4"></a></h2>
43 <span class="comment">% Stoc filter</span>
44
45 <div class="fragment"><pre>
46 fil1 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 191));
47 fil2 = filterbank(pl.pset(<span class="string">'binary'</span>, <span class="string">'yes'</span>, <span class="string">'id'</span>, 192));
48 fil3 = filterbank(miir());
49 <span class="comment">% build matrix</span>
50 wf = matrix(fil1,fil3,fil3,fil2,plist(<span class="string">'shape'</span>,[2 2]));
51 </pre></div>
52
53 <h2>Build input objects<a name="6"></a></h2>
54
55 <div class="fragment"><pre>
56
57 <span class="comment">% empty ao</span>
58 eao = ao();
59
60 <span class="comment">% exp_3_1</span>
61 os1 = matrix(o1_1,o12_1,plist(<span class="string">'shape'</span>,[2 1]));
62
63 <span class="comment">% exp_3_2</span>
64 os2 = matrix(o1_2,o12_2,plist(<span class="string">'shape'</span>,[2 1]));
65
66 <span class="comment">% Input signals</span>
67 iS = collection(is1,is2);
68
69 <span class="comment">% Fit Params</span>
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>};
71
72 nsecs = os1.objs(1).data.nsecs;
73 fs = os1.objs(1).data.fs;
74 npad = nsecs*fs;
75
76 <span class="comment">% set bounded params</span>
77 bdparams = {<span class="string">'del1'</span>,<span class="string">'del2'</span>};
78 bdvals = {[0.1 0.3],[0.1 0.3]};
79
80 </pre></div>
81
82 <h2>system model 1<a name="7"></a></h2>
83
84 <div class="fragment"><pre>
85
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>));
87 </pre></div>
88
89 <h2>Do Fit<a name="8"></a></h2>
90
91 <div class="fragment"><pre>
92
93 plfit = plist(<span class="keyword">...</span>
94 <span class="string">'FitParams'</span>,usedparams,<span class="keyword">...</span>
95 <span class="string">'Model'</span>,H,<span class="keyword">...</span>
96 <span class="string">'Input'</span>,iS,<span class="keyword">...</span>
97 <span class="string">'WhiteningFilter'</span>,wf,<span class="keyword">...</span>
98 <span class="string">'tol'</span>,1,<span class="keyword">...</span>
99 <span class="string">'Nloops'</span>,10,<span class="keyword">...</span>
100 <span class="string">'Npad'</span>,npad,<span class="keyword">...</span>
101 <span class="string">'Ncut'</span>,1e4);
102
103 opars1 = linfitsvd(os1,os2,plfit);
104 </pre></div>
105
106 <h2>system model 2<a name="9"></a></h2>
107
108 <div class="fragment"><pre>
109
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>));
111 </pre></div>
112
113 <h2>Set Model Alias<a name="10"></a></h2>
114
115 <div class="fragment"><pre>
116
117 plalias = plist(<span class="string">'nsecs'</span>,nsecs,<span class="string">'npad'</span>,npad,<span class="string">'fs'</span>,fs);
118 <span class="keyword">for</span> ii=1:numel(H2.objs)
119 H2.objs(ii).assignalias(H2.objs(ii),plalias);
120 <span class="keyword">end</span>
121 </pre></div>
122
123 <h2>Do fit with alias<a name="11"></a></h2>
124
125 <div class="fragment"><pre>
126
127 plfit2 = plist(<span class="keyword">...</span>
128 <span class="string">'FitParams'</span>,usedparams,<span class="keyword">...</span>
129 <span class="string">'Model'</span>,H2,<span class="keyword">...</span>
130 <span class="string">'BoundedParams'</span>,bdparams,<span class="keyword">...</span>
131 <span class="string">'BoundVals'</span>,bdvals,<span class="keyword">...</span>
132 <span class="string">'Input'</span>,iS,<span class="keyword">...</span>
133 <span class="string">'WhiteningFilter'</span>,wf,<span class="keyword">...</span>
134 <span class="string">'tol'</span>,1,<span class="keyword">...</span>
135 <span class="string">'Nloops'</span>,10,<span class="keyword">...</span><span class="comment"> % maximum number of fit iterations</span>
136 <span class="string">'Npad'</span>,npad,<span class="keyword">...</span>
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>
138
139 opars2 = linfitsvd(os1,os2,plfit2);
140 </pre></div>
141