The handbook of brain theory and neural networks

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The handbook of brain theory and neural networks

edited by Michael A. Arbib ; editorial advisory board, Shun-ichi Amari ... [et al.] ; editoral assistant, Prudence H. Arbib

MIT Press, c2003

2nd ed

Available at  / 77 libraries

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Note

Previous ed.: 1995

"A Bradford book."

Includes bibliographical references and index

Description and Table of Contents

Description

A new, dramatically updated edition of the classic resource on the constantly evolving fields of brain theory and neural networks. Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook of Brain Theory and Neural Networks presents the enormous progress made in recent years in the many subfields related to the two great questions: How does the brain work? and, How can we build intelligent machines? Once again, the heart of the book is a set of almost 300 articles covering the whole spectrum of topics in brain theory and neural networks. The first two parts of the book, prepared by Michael Arbib, are designed to help readers orient themselves in this wealth of material. Part I provides general background on brain modeling and on both biological and artificial neural networks. Part II consists of "Road Maps" to help readers steer through articles in part III on specific topics of interest. The articles in part III are written so as to be accessible to readers of diverse backgrounds. They are cross-referenced and provide lists of pointers to Road Maps, background material, and related reading. The second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. It contains 287 articles, compared to the 266 in the first edition. Articles on topics from the first edition have been updated by the original authors or written anew by new authors, and there are 106 articles on new topics.

Table of Contents

  • Part 1 Background: how to use part 1
  • introducing the neuron
  • levels and styles of analysis
  • dynamics and adaptation in neural networks. Part 2 Road maps: the meta-map
  • connectionism - psychology, linguistics and artificial intelligence
  • dynamics, self-organization and cooperativity
  • learning in artificial neural networks
  • applications and implementations
  • biological neurons and networks
  • sensory systems
  • plasticity in development and learning
  • motor control. Part 3 Articles. (Part contents).

by "Nielsen BookData"

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