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Neural Networks for Pattern Recognition

by Christopher M. Bishop

Clarendon Press

Paperback 504 pages English Jan 18, 1996

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This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts, the book examines techniques for modeling probability density functions and the properties and merits of the multi-layer perceptron and radial basis function network models. Also covered are various forms of error functions, principal algorithms for error function minimalization, learning and generalization in neural networks, and Bayesian techniques and their applications. Designed as a text, with over 100 exercises, this fully up-to-date work will benefit anyone involved in the fields of neural computation and pattern recognition.
Author:
Christopher M. Bishop
Publisher:
Clarendon Press
Publication Date:
Jan 18, 1996
Number of pages:
504 pages
Language:
English
Binding:
Paperback
ISBN-10:
0198538642
ISBN-13:
9780198538646