view m-toolbox/html_help/help/ug/sigproc_iir_content.html @ 51:9d5c88356247
database-connection-manager
Make unit tests database connection parameters configurable
author
Daniele Nicolodi <nicolodi@science.unitn.it>
date
Wed, 07 Dec 2011 17:24:37 +0100 (2011-12-07)
parents
f0afece42f48
children
line source
+ − <p>
+ − 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
+ − </p>
+ − <div align="center">
+ − <IMG src="images/sigproc_7.png" width="283" height="56" align="middle" border="0">
+ − </div>
+ − <p>
+ − 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].
+ − </p>
+ − <h2><a name="IIRbuild">Creating a IIR filter in the LTPDA</a></h2>
+ −
+ − The LTPDA Toolbox allows the implementation of IIR filters by means of the <a href="pzmodel_filter.html"> miir class</a>.
+ −
+ − <h2><a name="IIRplist">Creating from a plist</a></h2>
+ − <p>
+ − 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.
+ − </p>
+ − <div class="fragment"><pre>
+ −
+ − pl = plist(<span class="string">'type'</span>, <span class="string">'highpass'</span>, ...
+ − <span class="string">'order'</span>, 1, ...
+ − <span class="string">'gain'</span>, 2.0, ...
+ − <span class="string">'fs'</span>, 10, ...
+ − <span class="string">'fc'</span>, 0.2);
+ − f = miir(pl)
+ − </pre></div>
+ −
+ − <h2><a name="IIRpzmodel">Creating from a pzmodel</a></h2>
+ − <p>
+ − IIR filters can also be <a href="pzmodel_filter.html"> created from a pzmodel </a>.
+ − </p>
+ − <h2><a name="IIRdiff">Creating from a difference equation</a></h2>
+ − <p>
+ − 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:
+ − </p>
+ −
+ − <div align="center">
+ − <IMG src="images/sigproc_9.png" width="299" height="28" align="middle" border="0">
+ − </div>
+ −
+ − <p><br></p>
+ −
+ − <div class="fragment"><pre>
+ −
+ − a = [0.5 -0.01];
+ − b = [1 0.1];
+ − fs = 1;
+ − f = miir(a,b,fs)
+ − </pre></div>
+ −
+ − <p>
+ − <br>
+ − Notice that the convetion used in this function is the one described in the <a href="sigproc_dfilt.html"> Digital filters classification</a> section
+ − </p>
+ −
+ − <h2><a name="IIRimport">Importing an existing model</a></h2>
+ − <p>
+ − The miir constructor also accepts as an input existing models in different formats:
+ − </p>
+ − <li>
+ − <li><p>LISO files:<p>
+ − <div class="fragment"><pre>
+ − f = miir(<span class="string">'foo_iir.fil'</span>)
+ − </pre></div>
+ − </li>
+ − <li><p>XML files:</p>
+ − <div class="fragment"><pre>
+ − f = miir(<span class="string">'foo_iir.xml'</span>)
+ − </pre></div>
+ − <li><p>MAT files:</p>
+ − <div class="fragment"><pre>
+ − f = miir(<span class="string">'foo_iir.mat'</span>)
+ − </pre></div>
+ − </li>
+ − <li><p>From repository:</p>
+ − <div class="fragment"><pre>
+ − 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>, []))
+ − </pre></div>
+ − </li>
+ − </ul>
+ −