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Inhaltsangabe
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.
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Críticas
"...of interest to those following the neural net field...takes off from discoveries that link areas of physics with the emerging neural network paradigm." Intelligence Monthly
"...regard this book as an opening of a discussion--undoubtedly a very qualified one." Journal of Mathematical Psychology
Reseña del editor
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.
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Modeling Brain Function : The World of Attractor Neural Networks
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Cambridge University Press, 1989
ISBN 10: 0521361001
ISBN 13: 9780521361002
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Modeling Brain Function: The World of Attractor Neural Networks
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ISBN 10: 0521361001
ISBN 13: 9780521361002
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Modeling Brain Function : The World of Attractor Neural Networks
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Cambridge University Press, 1989
ISBN 10: 0521361001
ISBN 13: 9780521361002
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Modeling Brain Function: The World of Attractor Neural Networks
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Modeling Brain Function: The World of Attractor Neural Networks
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Modeling Brain Function: The World of Attractor Neural Networks
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Modeling Brain Function: The World of Attractor Neural Networks
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ISBN 13: 9780521361002
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Modeling Brain Function: The Worldof Attractor Neural Networks
Verlag:
Cambridge University Press, United Kingdom, 1989
ISBN 10: 0521361001
ISBN 13: 9780521361002
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Hardcover. Zustand: Very Good. 8vo. Hardcover. Pp. 504. Very good condition, some mild shelf-wear but pages are unmarked and crisp. One of the most exciting and rewarding studies in its respective field, this book introduces and explains the techniques brought from physics to the study of neural networks. Accessibly written and synthesizing a wide breadth of research - from physicists, scientists, computer technicians - the author presents a coherent presentation of basic ideas regarding the mechanisms of the human brain. Daniel Amit is a professor at the Racah Institute of Physics, Jerusalem. Since 1983, he has made neural networks his central subject of investigation. He is the Honorary Editor of the interdisciplinary journal NETWORK. Bestandsnummer des Verkäufers 036312
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