Neural Networks for Pattern Recognition

ISBN-10: 0198538642

ISBN-13: 9780198538646

Edition: 1995

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Description:

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.
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Book details

List price: $105.00
Copyright year: 1995
Publisher: Oxford University Press, Incorporated
Publication date: 1/18/1996
Binding: Paperback
Pages: 504
Size: 6.25" wide x 9.25" long x 1.25" tall
Weight: 1.012
Language: English

Geoffrey Hinton is Professor of Computer Science at the University of Toronto.

Statistical pattern recognition
Probability density estimation
Single-layer networks
The multi-layer perceptron
Radial basis functions
Error
Parameter optimization algorithms
Pre-processing and feature extraction
Learning and generalization
Bayesian techniques
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