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<document xmlns="http://cnx.rice.edu/cnxml" xmlns:md="http://cnx.rice.edu/mdml/0.4" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:bib="http://bibtexml.sf.net/" id="new1">
  <name>Why Transforms?</name>
  <metadata>
  <md:version>2.0</md:version>
  <md:created>2003/01/13</md:created>
  <md:revised>2003/01/13</md:revised>
  <md:authorlist>
      <md:author id="schniter">
      <md:firstname>Phil</md:firstname>
      
      <md:surname>Schniter</md:surname>
      <md:email>schniter@ee.eng.ohio-state.edu</md:email>
    </md:author>
  </md:authorlist>

  <md:maintainerlist>
    <md:maintainer id="charlet">
      <md:firstname>Charlet</md:firstname>
      
      <md:surname>Reedstrom</md:surname>
      <md:email>charlet@rice.edu</md:email>
    </md:maintainer>
    <md:maintainer id="schniter">
      <md:firstname>Phil</md:firstname>
      
      <md:surname>Schniter</md:surname>
      <md:email>schniter@ee.eng.ohio-state.edu</md:email>
    </md:maintainer>
  </md:maintainerlist>
  
  <md:keywordlist>
    <md:keyword>transforms</md:keyword>
  </md:keywordlist>

  <md:abstract/>
</metadata>


  <content>
      <para id="p00">
	In the field of signal processing we frequently encounter the
	use of <term>transforms</term>. Transforms are named such because they
	take a signal and <emphasis>transform</emphasis> it into
	another signal, hopefully one which is easier to process or
	analyze than the original. Essentially, transforms are used to
	manipulate signals such that their most important
	characteristics are made plainly evident. To isolate a
	signal's important characteristics, however, one must employ a
	transform that is well matched to that signal. For example,
	the Fourier transform, while well matched to certain classes
	of signal, does not efficiently extract information about
	signals in other classes. This latter fact motivates our
	development of the wavelet transform. 
      </para> 
  </content>
  
</document>
