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Synopsis
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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About the Author
Chris Bishop is at Aston University.
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- PublisherClarendon Press
- Publication date1996
- ISBN 10 0198538642
- ISBN 13 9780198538646
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages504
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Neural Networks for Pattern Recognition (Advanced Texts in Econometrics (Paperback))
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