An Introduction to the Modeling of Neural Networks (Collection Alea-Saclay: Monographs and Texts in Statistical Physics)

An Introduction to the Modeling of Neural Networks (Collection Alea-Saclay: Monographs ...

Pierre Peretto

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An Introduction to the Modeling of Neural Networks (Colle...
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    An Introduction to the Modeling of Neural Networks (Collection Alea-Saclay: Monographs and Texts in Statistical Physics)

    $96.60 USD
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    Book Details

    Author
    Pierre Peretto
    Publisher
    Cambridge University Press
    Format
    Paperback
    Language
    English
    Category
    Certification
    Condition
    New
    ISBN-13
    9780521424875
    ISBN-10
    0521424879

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    Product description

    ISBN: 0521424879

    Author: Peretto, Pierre

    Condition: New

    This text is a graduate-level introduction to neural networks, focusing on current theoretical models, examining what these models can reveal about how the brain functions, and discussing the ramifications for psychology, artificial intelligence, and the construction of a new generation of intelligent computers. The book is divided into four parts. The first part gives an account of the anatomy of the central nervous system, followed by a brief introduction to neurophysiology. The second part is devoted to the dynamics of neuronal states, and demonstrates how very simple models may stimulate associative memory. The third part of the book discusses models of learning, including detailed discussions on the limits of memory storage, methods of learning and their associated models, associativity, and error correction. The final section of the book reviews possible applications of neural networks in artificial intelligence, expert systems, optimization problems, and the construction of actual neuronal supercomputers, with the potential for one-hundred fold increase in speed over contemporary serial machines.

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    An Introduction to the Modeling of Neural Networks (Collection Alea-Saclay: Monographs and Texts in Statistical Physics)

    $96.60 USD
     per 

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