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Neural Nets and Artificial Intelligence.

Discusses neural nets in relation to contemporary studies of artificial intelligence. Reliable computing with unreliable neurons; Synaptic modification during learning; Background on the problem of pattern classification; Limitations of elementary perceptrons; Use of neural nets for prediction and s...

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Published in:Daedalus: Journal of the American Academy of Arts & Sciences Vol. 117; no. 1; pp. 85 - 122
Main Authors: Cowan, Jack D., Sharp, David H.
Format: Article
Published: MIT Press Winter88
Subjects:
Artificial neural networks
Artificial intelligence
Pattern perception
Perceptrons
Pattern recognition systems
Online Access:View this record in EBSCOhost
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        atl: Neural Nets and Artificial Intelligence.
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          Cowan, Jack D.
          Sharp, David H.
        affil:
          Professor of Applied Mathematics and Theoretical Biology, Department of Mathematics, University of Chicago
          Theoretical physicist, Theory Division of Los Alamos National Laboratory
      su:
        Artificial neural networks
        Artificial intelligence
        Pattern perception
        Perceptrons
        Pattern recognition systems
      sug:
        subj:
          Artificial neural networks
          Artificial intelligence
          Pattern perception
          Perceptrons
          Pattern recognition systems
      ab: Discusses neural nets in relation to contemporary studies of artificial intelligence. Reliable computing with unreliable neurons; Synaptic modification during learning; Background on the problem of pattern classification; Limitations of elementary perceptrons; Use of neural nets for prediction and simulation.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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