| Title | : | Neural Networks for Pattern Recognition (Advanced Texts in Econometrics (Paperback)) |
| Author | : | |
| Rating | : | |
| ISBN | : | 0198538642 |
| ISBN-10 | : | 9780198538646 |
| Language | : | English |
| Format Type | : | Paperback |
| Number of Pages | : | 502 |
| Publication | : | First published January 18, 1996 |
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.
Neural Networks for Pattern Recognition (Advanced Texts in Econometrics (Paperback)) Reviews
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A great book on the use of neural network as they apply to pattern recognition. This book is understandably heavy on the mathematical aspects of things, but the author does so with a grain of salt. This is definitely not a mathematics book.
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intro to neural networks
