<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0">
  <channel>
    <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/170541</link>
    <title>MATLAB Central Newsreader - [MxN] for principle component analysis (PCA)</title>
    <description>Feed for thread: [MxN] for principle component analysis (PCA)</description>
    <language>en-us</language>
    <copyright>&amp;copy;1994-2012 by MathWorks, Inc.</copyright>
    <webmaster>webmaster@mathworks.com</webmaster>
    <generator>MATLAB Central Newsreader</generator>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <ttl>60</ttl>
    <image>
      <title>MathWorks</title>
      <url>http://www.mathworks.com/images/membrane_icon.gif</url>
    </image>
    <item>
      <pubDate>Thu, 05 Jun 2008 22:14:27 -0400</pubDate>
      <title>[MxN] for principle component analysis (PCA)</title>
      <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/170541#436100</link>
      <author>Nate</author>
      <description>I am trying to create a matrix [MxN] for principle component analysis.&lt;br&gt;
My problem is that my waveforms do not all have the same vector length&lt;br&gt;
N, there is a difference of 15 to 100 data points. I am unsure what&lt;br&gt;
type of algorithm to use, or how in general to adjust the waveforms to&lt;br&gt;
the same vector length N.&lt;br&gt;
&lt;br&gt;
I know that this will change the frequency of the signal slightly but&lt;br&gt;
I am not so concerned the, with that slight change.  I am looking for&lt;br&gt;
identifying features over one rotation of the device one rotation may&lt;br&gt;
take a few milliseconds longer so the waveform vector has more data&lt;br&gt;
points. I need those vectors to contain the same number of points.&lt;br&gt;
&lt;br&gt;
A thought that I had was to add zeros to the end of each waveform&lt;br&gt;
making them all length N but I am unsure how that would effect PCA, if&lt;br&gt;
any one knows that would also be helpful information.&lt;br&gt;
&lt;br&gt;
Nate</description>
    </item>
    <item>
      <pubDate>Fri, 11 Jul 2008 19:10:26 -0400</pubDate>
      <title>Re: [MxN] for principle component analysis (PCA)</title>
      <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/170541#442555</link>
      <author>ahmed</author>
      <description>hi &lt;br&gt;
i think it is better for you to start with this paper: (A &lt;br&gt;
tutorial on Principal Components Analysis by Lindsay I &lt;br&gt;
Smith) you can found it in the internet</description>
    </item>
  </channel>
</rss>

