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Hardcover | Out of Print | 1134 pp. | 8.6 x 10.9 in | June 1995 | ISBN: 9780262011488
Paperback | Out of Print | 1134 pp. | 8.6 x 10.9 in | September 1998 | ISBN: 9780262511025
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The Handbook of Brain Theory and Neural Networks


In hundreds of articles by experts from around the world, and in overviews and "road maps" prepared by the editor, The Handbook of Brain Theory and Neural Networks charts the immense progress made in recent years in many specific areas related to two great questions: How does the brain work? and How can we build intelligent machines?While many books have appeared on limited aspects of one subfield or another of brain theory and neural networks, the Handbook covers the entire sweep of topics -- from detailed models of single neurons, analyses of a wide variety of biological neural networks, and connectionist studies of psychology and language, to mathematical analyses of a variety of abstract neural networks, and technological applications of adaptive, artificial neural networks.The excitement, and the frustration, of these topics is that they span such a broad range of disciplines including mathematics, statistical physics and chemistry, neurology and neurobiology, and computer science and electrical engineering as well as cognitive psychology, artificial intelligence, and philosophy. Thus, much effort has gone into making the Handbook accessible to readers with varied backgrounds while still providing a clear view of much of the recent, specialized research in specific topics.The heart of the book, part III, comprises of 267 original articles by leaders in the various fields, arranged alphabetically by title. Parts I and II, written by the editor, are designed to help readers orient themselves to this vast range of material. Part I, Background , introduces several basic neural models, explains how the present study of brain theory and neural networks integrates brain theory, artificial intelligence, and cognitive psychology, and provides a tutorial on the concepts essential for understanding neural networks as dynamic, adaptive systems. Part II, Road Maps , provides entry into the many articles of part III through an introductory "Meta-Map" and twenty-three road maps, each of which tours all the Part III articles on the chosen theme.

About the Editor

Michael Arbib has played a leading role at the interface of neuroscience and computer science ever since his first book, Brains, Machines, and Mathematics. From Neuron to Cognition provides a worthy pedagogical sequel to his widely acclaimed Handbook of Brain Theory and Neural Networks. After thirty years at University of Southern California he is now pursuing interests in “how the brain got language” and “neuroscience for architecture” in San Diego.


Choice Outstanding Academic Title, 1996.