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Cleanup
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 18:04:34 +0100
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1 <p>
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2 Infinite Impulse Response filters are those filters present a non-zero infinite length response when excited with a very brief (ideally an infinite peak) input signal. A linear causal IIR filter can be described by the following difference equation
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3 </p>
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4 <div align="center">
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5 <IMG src="images/sigproc_7.png" width="283" height="56" align="middle" border="0">
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6 </div>
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7 <p>
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8 This operation describe a recursive system, i.e. a system that depends on current and past samples of the input x[n], but also on the output data stream y[n].
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9 </p>
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10 <h2><a name="IIRbuild">Creating a IIR filter in the LTPDA</a></h2>
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11
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12 The LTPDA Toolbox allows the implementation of IIR filters by means of the <a href="pzmodel_filter.html"> miir class</a>.
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13
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14 <h2><a name="IIRplist">Creating from a plist</a></h2>
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15 <p>
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16 The following example creates an order 1 highpass filter with high frequency gain 2. Filter is designed for 10 Hz sampled data and has a cut-off frequency of 0.2 Hz.
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17 </p>
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18 <div class="fragment"><pre>
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19
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20 pl = plist(<span class="string">'type'</span>, <span class="string">'highpass'</span>, ...
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21 <span class="string">'order'</span>, 1, ...
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22 <span class="string">'gain'</span>, 2.0, ...
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23 <span class="string">'fs'</span>, 10, ...
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24 <span class="string">'fc'</span>, 0.2);
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25 f = miir(pl)
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26 </pre></div>
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27
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28 <h2><a name="IIRpzmodel">Creating from a pzmodel</a></h2>
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29 <p>
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30 IIR filters can also be <a href="pzmodel_filter.html"> created from a pzmodel </a>.
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31 </p>
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32 <h2><a name="IIRdiff">Creating from a difference equation</a></h2>
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33 <p>
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34 Alternatively, the filter can be defined in terms of two vectors specifying the coefficients of the filter and the sampling frequency. The following example creates a IIR filter with sampling frequency 1 Hz and the following recursive equation:
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35 </p>
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36
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37 <div align="center">
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38 <IMG src="images/sigproc_9.png" width="299" height="28" align="middle" border="0">
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39 </div>
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40
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41 <p><br></p>
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42
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43 <div class="fragment"><pre>
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44
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45 a = [0.5 -0.01];
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46 b = [1 0.1];
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47 fs = 1;
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48 f = miir(a,b,fs)
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49 </pre></div>
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50
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51 <p>
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52 <br>
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53 Notice that the convetion used in this function is the one described in the <a href="sigproc_dfilt.html"> Digital filters classification</a> section
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54 </p>
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55
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56 <h2><a name="IIRimport">Importing an existing model</a></h2>
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57 <p>
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58 The miir constructor also accepts as an input existing models in different formats:
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59 </p>
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60 <li>
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61 <li><p>LISO files:<p>
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62 <div class="fragment"><pre>
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63 f = miir(<span class="string">'foo_iir.fil'</span>)
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64 </pre></div>
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65 </li>
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66 <li><p>XML files:</p>
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67 <div class="fragment"><pre>
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68 f = miir(<span class="string">'foo_iir.xml'</span>)
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69 </pre></div>
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70 <li><p>MAT files:</p>
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71 <div class="fragment"><pre>
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72 f = miir(<span class="string">'foo_iir.mat'</span>)
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73 </pre></div>
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74 </li>
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75 <li><p>From repository:</p>
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76 <div class="fragment"><pre>
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77 f = miir(plist(<span class="string">'hostname'</span>, <span class="string">'localhost'</span>, <span class="string">'database'</span>, <span class="string">'ltpda'</span>, <span class="string">'ID'</span>, []))
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78 </pre></div>
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79 </li>
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80 </ul>
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