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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="new0">
  <name>Hilbert Space Theory</name>
  <metadata>
  <md:version>2.0</md:version>
  <md:created>2003/01/15</md:created>
  <md:revised>2003/01/15</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>Hilbert Space Theory</md:keyword>
    <md:keyword>review</md:keyword>
  </md:keywordlist>

  <md:abstract/>
</metadata>


  <content>
    <para id="para1">
      Hilbert spaces provide the mathematical foundation for signal
      processing theory.  In this section we attempt to clearly
      define some key Hilbert space concepts like <cnxn document="m10419" strength="9">vectors</cnxn>, <cnxn document="m10428" strength="9">norms</cnxn>, <cnxn document="m10430" strength="9">inner products</cnxn>, <cnxn document="m10434" strength="9">subspaces</cnxn>, <cnxn document="m10434" strength="9">orthogonality</cnxn>, <cnxn document="m10434" strength="9">orthonormal bases</cnxn>, and <cnxn document="m10434" strength="9">projections</cnxn>.  The intent is not to bury you
      in mathematics, but to familiarize you with the terminology,
      provide intuition, and leave you with a "lookup table" for
      future reference.
    </para>
  </content>
  
</document>
