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Introduction To The Theory Of Neural Computation (Santa Fe Institute Series)

John A. Hertz, Anders S. Krogh, Richard G. Palmer




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 | #543179 in Books |  1991-06-24 | Original language:English | PDF # 1 |  9.00 x.80 x6.00l,1.11 | File type: PDF | 350 pages

||0 of 0 people found the following review helpful.| To really enjoy this book|By Waseem|To really enjoy this book, one has to co-read a book in Statistical (Quantum) Mechanics, which in itself could be very involved. However, if you follow "Statistical Mechanics: A Survival Guide" by A. M. Glazer it will be an enjoyable read. The idea is to see how theoretical physics has informed the information processing in neural networks.||.com |This book comprehensively discusses the neural network models from a statistical mechanics perspective. It starts with one of the most influential developments in the theory of neural networks: Hopfield's analysis of networks with symmetric connections

Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.

You can specify the type of files you want, for your gadget.Introduction To The Theory Of Neural Computation (Santa Fe Institute Series)   |  John A. Hertz, Anders S. Krogh, Richard G. Palmer. I really enjoyed this book and have already told so many people about it!

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