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Dynamic Interactions in Neural Networks: Models and Data: Models and Data (Research Notes in Neural Computing) (Volume 1) - Tapa blanda
Sinopsis
The study of neural networks is enjoying a great renaissance, both in computational neuroscience, the development of information processing models of living brains, and in neural computing, the use of neurally inspired concepts in the construction of "intelligent" machines. Thus the title of this volume has two interpretations: It presents models and data on the dynamic interactions occurring in the brain, and it exhibits the dynamic interactions between research in computational neuroscience and in neural computing, as scientists seek to find common principles to guide the understanding of the living brain and the design of artificial neural networks. This collection of contributions presents the current state of research, future trends and open problems in an exciting field of today's science.
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Reseña del editor
This is an exciting time. The study of neural networks is enjoying a great renaissance, both in computational neuroscience - the development of information processing models of living brains - and in neural computing - the use of neurally inspired concepts in the construction of "intelligent" machines. Thus the title of this volume, Dynamic Interactions in Neural Networks: Models and Data can be given two interpretations. We present models and data on the dynamic interactions occurring in the brain, and we also exhibit the dynamic interactions between research in computational neuroscience and in neural computing, as scientists seek to find common principles that may guide us in the understanding of our own brains and in the design of artificial neural networks. In fact, the book title has yet a third interpretation. It is based on the U. S. -Japan Seminar on "Competition and Cooperation in Neural Nets" which we organized at the University of Southern California, Los Angeles, May 18-22, 1987, and is thus the record of interaction of scientists on both sides of the Pacific in advancing the frontiers of this dynamic, re-born field. The book focuses on three major aspects of neural network function: learning, perception, and action. More specifically, the chapters are grouped under three headings: "Development and Learning in Adaptive Networks," "Visual Function", and "Motor Control and the Cerebellum.
Reseña del editor
The study of neural networks is enjoying a great renaissance, both in computational neuroscience, the development of information processing models of living brains, and in neural computing, the use of neurally inspired concepts in the construction of "intelligent" machines. Thus the title of this volume has two interpretations: It presents models and data on the dynamic interactions occurring in the brain, and it exhibits the dynamic interactions between research in computational neuroscience and in neural computing, as scientists seek to find common principles to guide the understanding of the living brain and the design of artificial neural networks. This collection of contributions presents the current state of research, future trends and open problems in an exciting field of today's science.
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- EditorialSpringer
- Año de publicación2013
- ISBN 10 0387968938
- ISBN 13 9780387968933
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas292
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Dynamic interactions in neural networks
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Dynamic Interactions in Neural Networks: Models and Data Dynamic Interactions in Neural Networks: Models and Data. (Research Notes in Neural Commputing, Vol. 1)
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Springer Verlag, 1989
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ISBN 13: 9780387968933
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Dynamic Interactions in Neural Networks: Models and Data. Volume 1.
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Dynamic Interactions in Neural Networks: Models and Data. Volume 1.
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ISBN 13: 9780387968933
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Dynamic Interactions in Neural Networks: Models and Data
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ISBN 10: 0387968938
ISBN 13: 9780387968933
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Tapa blanda
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Dynamic Interactions in Neural Networks: Models and Data.; (Research Notes in Neural Commputing, Vol. 1)
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ISBN 13: 9780387968933
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Dynamic Interactions In Neural Networks - Models And Data
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Dynamic Interactions in Neural Networks
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