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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"...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
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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Zustand: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780521361002. Bestandsnummer des Verkäufers 8249839
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Zustand: Gut. Zustand: Gut | Seiten: 528 | Sprache: Englisch | Produktart: Bücher. Bestandsnummer des Verkäufers 25465121/203
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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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