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Applied Artificial Higher Order Neural Networks for Control and Recognition

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Applied Artificial Higher Order Neural Networks for Control and Recognition
Περιγραφή: In recent years, Higher Order Neural Networks (HONNs) have been widely adopted by researchers for applications in control signal generating, pattern recognition, nonlinear recognition, classification, and predition of control and recognition scenarios. Due to the fact that HONNs have been proven to be faster, more accurate, and easier to explain than traditional neural networks, their applications are limitless. Applied Artificial Higher Order Neural Networks for Control and Recognition explores the ways in which higher order neural networks are being integrated specifically for intelligent technology applications. Emphasizing emerging research, practice, and real-world implementation, this timely reference publication is an essential reference source for researchers, IT professionals, and graduate-level computer science and engineering students.
Συγγραφείς: Ming Zhang
Resource Type: eBook.
Θέματα: Automatic control--Data processing, Pattern recognition systems--Data processing, Neural networks (Computer science)
Categories: COMPUTERS / Data Science / Neural Networks, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition
Βάση Δεδομένων: eBook Index
FullText Text:
  Availability: 0
Header DbId: edsebk
DbLabel: eBook Index
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RelevancyScore: 925
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 924.640747070313
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  Data: Applied Artificial Higher Order Neural Networks for Control and Recognition
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  Data: In recent years, Higher Order Neural Networks (HONNs) have been widely adopted by researchers for applications in control signal generating, pattern recognition, nonlinear recognition, classification, and predition of control and recognition scenarios. Due to the fact that HONNs have been proven to be faster, more accurate, and easier to explain than traditional neural networks, their applications are limitless. Applied Artificial Higher Order Neural Networks for Control and Recognition explores the ways in which higher order neural networks are being integrated specifically for intelligent technology applications. Emphasizing emerging research, practice, and real-world implementation, this timely reference publication is an essential reference source for researchers, IT professionals, and graduate-level computer science and engineering students.
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RecordInfo BibRecord:
  BibEntity:
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      – Code: 629.895632
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Automatic control--Data processing
        Type: general
      – SubjectFull: Pattern recognition systems--Data processing
        Type: general
      – SubjectFull: Neural networks (Computer science)
        Type: general
    Titles:
      – TitleFull: Applied Artificial Higher Order Neural Networks for Control and Recognition
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          Name:
            NameFull: Ming Zhang
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            NameFull: Ming Zhang
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2016
            – D: 12
              M: 05
              Type: profile
              Y: 2016
          Identifiers:
            – Type: isbn-print
              Value: 9781522500636
            – Type: isbn-electronic
              Value: 9781522500643
            – Type: isbn-electronic
              Value: 9781522500650
          Titles:
            – TitleFull: Applied Artificial Higher Order Neural Networks for Control and Recognition
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