Publisher description for Neural networks for pattern recognition / Christopher M. Bishop.


Bibliographic record and links to related information available from the Library of Congress catalog


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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 modelling 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.


Library of Congress subject headings for this publication:
Neural networks (Computer science)
Pattern recognition systems.