comparison m-toolbox/html_help/help/ug/sigproc_dfilt.html @ 0:f0afece42f48

Import.
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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11 <title>Digital Filtering (LTPDA Toolbox)</title>
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21 <p style="font-size:1px;">&nbsp;</p>
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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=
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35
36 <h1 class="title"><a name="f3-12899" id="f3-12899"></a>Digital Filtering</h1>
37 <hr>
38
39 <p>
40 <p>
41 A digital filter is an operation that associates an input time series x[n] into an output one, y[n]. Methods developed in the LTPDA Toolbox deal with linear digital filters, i.e. those which fulfill that a linear combination of inputs results in a linear combination of outputs with the same coefficients (provided that these are not time dependent). In these conditions, the filter can be expressed as
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44 <IMG src="images/sigproc_1.png" width="173" height="55" align="center" border="0">
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46 <p>
47 described in these terms, the filter is completely described by the impulse response h[k], and can then be subdivided into the following classes:
48 </p>
49
50 <ul>
51 <li> Causal: if there is no output before input is fed in.
52 <div align="center">
53 <IMG src="images/sigproc_2.png" width="103" height="28" align="center" border="0">
54 </div>
55 </li>
56 <li> Stable: if finite input results in finite output.
57 <div align="center">
58 <IMG src="images/sigproc_3.png" width="105" height="55" align="center" border="0">
59 </div>
60 </li>
61 <li> Shift invariant: if time shift in the input results in a time shift in the output by the same amount.
62 <div align="center">
63 <IMG src="images/sigproc_4.png" width="84" height="28" align="center" border="0">
64 </div>
65 </li>
66 </ul>
67 <br>
68 <h2><a name="ARMA">Digital filters classification</a></h2>
69 <p>
70 Digital filters can be described as difference equations. If we consider an input time series x and an output y, three specific cases can then be distinguished:
71 </p>
72 <ul>
73 <li> Autoregressive (AR) process: the difference equation in this case is given by:
74 <div align="center">
75 <br>
76 <IMG src="images/sigproc_12.png" width="154" height="56" align="center" border="0">
77 </div>
78 <br>
79 AR processes can be also classified as <a href="sigproc_iir.html"> IIR Filters</a>.
80 <br>
81 <br></li>
82 <li> Moving Averrage (MA) process:the difference equation in this case is given by: <br>
83 <div align="center">
84 <br>
85 <IMG src="images/sigproc_11.png" width="156" height="56" align="center" border="0">
86 </div>
87 <br>
88 MA processes can be also classified as <a href="sigproc_fir.html"> FIR Filters</a>.
89 <br>
90 <br></li>
91 <li>Autoregressive Moving Average (ARMA) process: the difference equation in this case contains both an AR and a MA process:
92 <div align="center">
93 <br>
94 <IMG src="images/sigproc_7.png" width="283" height="56" align="center" border="0">
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111 <td align="left">Signal Processing in LTPDA</td>
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115 <td align="right">IIR Filters</td>
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