Modeling Brain Function: The World of Attractor Neural Networks

Daniel J. Amit

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Language: English

Published by Cambridge University Press, United Kingdom, Cambridge, 1992

0521421241 / 9780521421249

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Seller: WorldofBooks, Goring-By-Sea, WS, United KingdomWorldofBooks

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One of the most exciting and potentially rewarding areas of scientific research is the study of the principles and mechanisms underlying brain function. It is also of great promise to future generations of computers. A growing group of researchers, adapting knowledge and techniques from a wide range of scientific disciplines, have made substantial progress understanding memory, the learning process, and self organization by studying the properties of models of neural networks - idealized systems containing very large numbers of connected neurons, whose interactions give rise to the special qualities of the brain. This book introduces and explains the techniques brought from physics to the study of neural networks and the insights they have stimulated. It is written at a level accessible to the wide range of researchers working on these problems - statistical physicists, biologists, computer scientists, computer technologists and cognitive psychologists. The author presents a coherent and clear nonmechanical presentation of all the basic ideas and results. More technical aspects are restricted, wherever possible, to special sections and appendices in each chapter. The book is suitable as a text for graduate courses in physics, electrical engineering, computer science and biology. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

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Title
Modeling Brain Function: The World of Attractor Neural Networks
Author
Daniel J. Amit
Publisher
Cambridge University Press, United Kingdom, Cambridge
Publication year
1992
Condition
Very Good
Binding
Paperback
Language
English
ISBN 10
0521421241
ISBN 13
9780521421249
Item weight
871 grams
Dimensions
152.0 x 229.0

WorldofBooks

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