Neural Networks for Pattern Recognition

by Christopher M. Bishop

2020-11-24 03:11:26

This book provides the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts of pattern recognition, the book describes techniques for modelling pr... Read more
This book provides the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts of pattern recognition, the book describes techniques for modelling probability density functions, and discussesthe properties and relative merits of the multi-layer perceptron and radial basis function network models. It also motivates the use of various forms of error functions, and reviews the principal algorithms for error function minimization. As well as providing a detailed discussion of learningand generalization in neural networks, the book also covers the important topics of data processing, feature extraction, and prior knowledge. The book concludes with an extensive treatment of Bayesian techniques and their applications to neural networks. Less

Book Details

File size9.21 X 6.14 X 1.1 in
Print pages504
PublisherOxford University Press
Publication date June 1, 1994
LanguageEnglish
ISBN9780198538646

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