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  <titleInfo>
    <title>Recurrent neural networks for prediction</title>
    <subTitle>learning algorithms, architectures, and stability</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Mandic, Danilo P.</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
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  <name type="personal">
    <namePart>Chambers, Jonathon A.</namePart>
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    <place>
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    <publisher>John Wiley</publisher>
    <dateIssued>c2001</dateIssued>
    <dateIssued encoding="marc">2001</dateIssued>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
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    <extent>xxi, 285 p. : ill. ; 26 cm.</extent>
  </physicalDescription>
  <note type="statement of responsibility">Danilo P. Mandic, Jonathon A. Chambers.</note>
  <note>Includes bibliographical references (p. [267]-280) and index.</note>
  <subject authority="lcsh">
    <topic>Machine learning</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Neural networks (Computer science)</topic>
  </subject>
  <subject>
    <topic>Recurrent neural Networks for prediction</topic>
  </subject>
  <subject>
    <topic>საინჟინრო საქმე</topic>
  </subject>
  <subject>
    <topic>საინფორმაციო ტექნოლოგიები</topic>
  </subject>
  <subject>
    <topic>ფიზიკა</topic>
  </subject>
  <subject>
    <topic>მოლეკულური ბიოლოგია</topic>
  </subject>
  <subject>
    <topic>Молекулярная биология</topic>
  </subject>
  <subject>
    <topic>Физика</topic>
  </subject>
  <subject>
    <topic>Инженерное дело</topic>
  </subject>
  <subject>
    <topic>Информационные технологии</topic>
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  <classification authority="lcc">Q325.5 .M36 2001</classification>
  <classification authority="ddc" edition="21"/>
  <classification authority="udc">00+620.3+53+577 M-15</classification>
  <relatedItem type="series">
    <titleInfo>
      <title>Adaptive and learning systems for signal processing, communications, and control</title>
    </titleInfo>
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  <identifier type="isbn">0471495174 (alk. paper)</identifier>
  <identifier type="lccn">2001033418</identifier>
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