Mercurial > hg > ltpda
diff m-toolbox/html_help/help/ug/sigproc_polyfit.html @ 0:f0afece42f48
Import.
| author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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| date | Wed, 23 Nov 2011 19:22:13 +0100 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/m-toolbox/html_help/help/ug/sigproc_polyfit.html Wed Nov 23 19:22:13 2011 +0100 @@ -0,0 +1,85 @@ +<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" + "http://www.w3.org/TR/1999/REC-html401-19991224/loose.dtd"> + +<html lang="en"> +<head> + <meta name="generator" content= + "HTML Tidy for Mac OS X (vers 1st December 2004), see www.w3.org"> + <meta http-equiv="Content-Type" content= + "text/html; charset=us-ascii"> + + <title>Polynomial Fitting (LTPDA Toolbox)</title> + <link rel="stylesheet" href="docstyle.css" type="text/css"> + <meta name="generator" content="DocBook XSL Stylesheets V1.52.2"> + <meta name="description" content= + "Presents an overview of the features, system requirements, and starting the toolbox."> + </head> + +<body> + <a name="top_of_page" id="top_of_page"></a> + + <p style="font-size:1px;"> </p> + + <table class="nav" summary="Navigation aid" border="0" width= + "100%" cellpadding="0" cellspacing="0"> + <tr> + <td valign="baseline"><b>LTPDA Toolbox</b></td><td><a href="../helptoc.html">contents</a></td> + + <td valign="baseline" align="right"><a href= + "sigproc_fit.html"><img src="b_prev.gif" border="0" align= + "bottom" alt="Fitting Algorithms"></a> <a href= + "sigproc_linear_param_estimation_svd.html"><img src="b_next.gif" border="0" align= + "bottom" alt="Linear Parameter Estimation with Singular Value Decomposition"></a></td> + </tr> + </table> + + <h1 class="title"><a name="f3-12899" id="f3-12899"></a>Polynomial Fitting</h1> + <hr> + + <p> + <p> + <a href="matlab:doc('ao/polyfit')">polyfit.m</a> overloads the polyfit() function of MATLAB for Analysis Objects.<br/> + The script calls the following MATLAB functions: + <ul> + <li> polyfit.m </li> + <li> polyval.m </li> + </ul> + <h2><a name="usage">Usage</a></h2> + <div class="fragment"><pre> + <span class="comment">% CALL: b = polyfit(a, pl)</span> + <span class="comment">%</span> + <span class="comment">% Parameters: 'N' - degree of polynomial to fit</span> + <span class="comment">% 'coeffs' - (optional) coefficients</span> + <span class="comment">% formed e.g. by [p,s] = polyfit(x,y,N);</span> + </pre></div> + 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/> + Using the output of polyval.m the fitted data series is created and outputted as analysis object. +</p> + + + </p> + + <br> + <br> + <table class="nav" summary="Navigation aid" border="0" width= + "100%" cellpadding="0" cellspacing="0"> + <tr valign="top"> + <td align="left" width="20"><a href="sigproc_fit.html"><img src= + "b_prev.gif" border="0" align="bottom" alt= + "Fitting Algorithms"></a> </td> + + <td align="left">Fitting Algorithms</td> + + <td> </td> + + <td align="right">Linear Parameter Estimation with Singular Value Decomposition</td> + + <td align="right" width="20"><a href= + "sigproc_linear_param_estimation_svd.html"><img src="b_next.gif" border="0" align= + "bottom" alt="Linear Parameter Estimation with Singular Value Decomposition"></a></td> + </tr> + </table><br> + + <p class="copy">©LTP Team</p> +</body> +</html>