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  <titleInfo>
    <title>Fundamentals of Neural Networks</title>
    <subTitle>Architectures, Algorithms Application</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Fausett L</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <typeOfResource/>
  <originInfo>
    <place>
      <placeTerm type="text">Chennai</placeTerm>
    </place>
    <publisher>Pearson</publisher>
    <dateIssued>1994</dateIssued>
    <issuance/>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <extent>467pp</extent>
  </physicalDescription>
  <abstract>An exceptionally clear, thorough introduction to neural networks written at an elementary level. Written with the beginning student in mind, the text features systematic discussions of all major neural networks and fortifies the reader's understanding with many examples.
An exceptionally clear, thorough introduction to neural networks written at an elementary level. Written with the beginning student in mind, the text features systematic discussions of all major neural networks and fortifies the reader's understudy with many examples.</abstract>
  <subject authority="lcshac">
    <topic>Simple Neural Nets for Pattern Classification</topic>
  </subject>
  <subject authority="mesh">
    <topic>Pattern Association</topic>
  </subject>
  <subject authority="nal">
    <topic>Neural Networks Based on Competition</topic>
  </subject>
  <subject>
    <topic>Adaptive Resonance Theory</topic>
  </subject>
  <subject authority="csh">
    <topic>Backpropagation Neural Net</topic>
  </subject>
  <identifier type="isbn">9788131700532</identifier>
  <recordInfo>
    <recordCreationDate encoding="marc">251211</recordCreationDate>
    <recordChangeDate encoding="iso8601">20251211132606.0</recordChangeDate>
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