Price: $115.00 - $97.47
(as of Sep 11, 2024 04:20:36 UTC – Details)
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.
ASIN : 0198538642
Publisher : Oxford University Press, USA; 1st edition (January 18, 1996)
Language : English
Paperback : 502 pages
ISBN-10 : 9780198538646
ISBN-13 : 978-0198538646
Item Weight : 1.65 pounds
Dimensions : 1.12 x 9.19 x 6.19 inches
Customers say
Customers find the book’s introduction good and useful. They say it has the fundamentals covered very well. Opinions differ on the writing quality, with some finding it succinct and enlightening, while others say the exercises are not written to reinforce concepts in the chapter.
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