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Update utils.jquery * * * Update utils.jmysql.getsinfo
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
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1 <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"
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2 "http://www.w3.org/TR/1999/REC-html401-19991224/loose.dtd">
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3
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4 <html lang="en">
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5 <head>
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6 <meta name="generator" content=
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7 "HTML Tidy for Mac OS X (vers 1st December 2004), see www.w3.org">
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8 <meta http-equiv="Content-Type" content=
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9 "text/html; charset=us-ascii">
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10
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11 <title>Polynomial Fitting (LTPDA Toolbox)</title>
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12 <link rel="stylesheet" href="docstyle.css" type="text/css">
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13 <meta name="generator" content="DocBook XSL Stylesheets V1.52.2">
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14 <meta name="description" content=
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15 "Presents an overview of the features, system requirements, and starting the toolbox.">
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16 </head>
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18 <body>
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19 <a name="top_of_page" id="top_of_page"></a>
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20
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21 <p style="font-size:1px;">&nbsp;</p>
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22
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23 <table class="nav" summary="Navigation aid" border="0" width=
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24 "100%" cellpadding="0" cellspacing="0">
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25 <tr>
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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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29 "sigproc_fit.html"><img src="b_prev.gif" border="0" align=
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30 "bottom" alt="Fitting Algorithms"></a>&nbsp;&nbsp;&nbsp;<a href=
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31 "sigproc_linear_param_estimation_svd.html"><img src="b_next.gif" border="0" align=
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32 "bottom" alt="Linear Parameter Estimation with Singular Value Decomposition"></a></td>
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33 </tr>
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34 </table>
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35
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36 <h1 class="title"><a name="f3-12899" id="f3-12899"></a>Polynomial Fitting</h1>
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37 <hr>
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38
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39 <p>
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40 <p>
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41 <a href="matlab:doc('ao/polyfit')">polyfit.m</a> overloads the polyfit() function of MATLAB for Analysis Objects.<br/>
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42 The script calls the following MATLAB functions:
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43 <ul>
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44 <li> polyfit.m </li>
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45 <li> polyval.m </li>
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46 </ul>
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47 <h2><a name="usage">Usage</a></h2>
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48 <div class="fragment"><pre>
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49 <span class="comment">% CALL: b = polyfit(a, pl)</span>
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50 <span class="comment">%</span>
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51 <span class="comment">% Parameters: 'N' - degree of polynomial to fit</span>
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52 <span class="comment">% 'coeffs' - (optional) coefficients</span>
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53 <span class="comment">% formed e.g. by [p,s] = polyfit(x,y,N);</span>
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54 </pre></div>
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55 The MATLAB function polyfit.m finds the coefficients of the polynomial p(x) of degree N that fits the vector 'x' to the vector 'y', in a least squares sense.<br/> After this in the script <a href="matlab:doc('ao/polyfit')">polyfit.m</a> the function polyval.m is called, which evaluates the polynomial of order 'N' according to these coefficients. <br/>
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56 Using the output of polyval.m the fitted data series is created and outputted as analysis object.
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57 </p>
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58
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59
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60 </p>
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61
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62 <br>
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63 <br>
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64 <table class="nav" summary="Navigation aid" border="0" width=
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65 "100%" cellpadding="0" cellspacing="0">
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66 <tr valign="top">
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67 <td align="left" width="20"><a href="sigproc_fit.html"><img src=
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68 "b_prev.gif" border="0" align="bottom" alt=
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69 "Fitting Algorithms"></a>&nbsp;</td>
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70
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71 <td align="left">Fitting Algorithms</td>
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72
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73 <td>&nbsp;</td>
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74
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75 <td align="right">Linear Parameter Estimation with Singular Value Decomposition</td>
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76
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77 <td align="right" width="20"><a href=
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78 "sigproc_linear_param_estimation_svd.html"><img src="b_next.gif" border="0" align=
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79 "bottom" alt="Linear Parameter Estimation with Singular Value Decomposition"></a></td>
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80 </tr>
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81 </table><br>
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82
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83 <p class="copy">&copy;LTP Team</p>
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84 </body>
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85 </html>