Introduction to the Theory of Neural Computation (Santa Fe Institute Studies in the Sciences of Complexity)

Hertz, John/ Krogh, Anders/ Palmer, Richard G.

ISBN 10: 0201515601 / ISBN 13: 9780201515602

Published by Perseus Books, 1991

About this Item

352 pages. 9.25x6.50x0.75 inches. In Stock. Seller Inventory # x-0201515601

Bibliographic Details

Title: Introduction to the Theory of Neural ...

Publisher: Perseus Books

Publication Date: 1991

Binding: Paperback

Condition: Brand New

About this title

Synopsis:

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.

Review:

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 using the spin system approach and using the notion of an energy function from physics. Introduction to the Theory of Neural Computation uses these powerful tools to analyze neural networks as associative memory stores and solvers of optimization problems. A detailed analysis of multi-layer networks and recurrent networks follow. The book ends with chapters on unsupervised learning and a formal treatment of the relationship between statistical mechanics and neural networks. Little information is provided about applications and implementations, and the treatment of the material reflects the background of the authors as physicists. However the book is essential for a solid understanding of the computational potential of neural networks. Introduction to the Theory of Neural Computation assumes that the reader is familiar with undergraduate level mathematics, but does not have any background in physics. All of the necessary tools are introduced in the book.