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NEURAL NETWORKS FOR PATTERN RECOGNITION
Published by
Oxford University Press, 2005
ISBN 10: 0195667999
ISBN 13: 9780195667998
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paperback
Seller: AwesomeBooks, Wallingford, United Kingdom
Seller rating 5 out of 5 stars
paperback. Condition: Very Good. NEURAL NETWORKS FOR PATTERN RECOGNITION This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. . Seller Inventory # 7719-9780195667998
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NEURAL NETWORKS FOR PATTERN RECOGNITION
Published by
Oxford University Press -, 2005
ISBN 10: 0195667999
ISBN 13: 9780195667998
Used
paperback
Seller: Bahamut Media, Reading, United Kingdom
Seller rating 5 out of 5 stars
paperback. Condition: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee. Seller Inventory # 6545-9780195667998
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Neural Networks for Pattern Recognition
Published by
Oxford University Press, New Delhi, India, 2003
ISBN 10: 0195667999
ISBN 13: 9780195667998
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First Edition
Seller: BIBLIOPE by Calvello Books, Oakland, CA, U.S.A.
Seller rating 4 out of 5 stars
Paperback. Condition: very good. First Indian Edition. Octavo in red and green wraps; illustrations; References; Index; 482p. "In this textbook, Chris Bishop provides the first comprehensive treatment of feed-forward networks from the perspective of statistical pattern recognition. After introducing the basic concepts of pattern recognition, he describes techniques for modelling probability density functions, and discusses the properties and relative merits of the multi-layer perceptron and radial basis function network models. He also motivates the use of various forms of error function, and reviews the principal algorithms for error function minimization. There is a detailed discussion of learning and generalization in neural networks, and the important topics of data processing, feature extraction, and prior knowledge are also covered. He concludes with an extensive treatment of Bayesian techniques and their applications to neural networks." --Back cover. Includes: 129 Graded exercises, a self-containd introduction to statistical pattern recognition, and an extensive discussion of Bayesian methods. A very good (-) copy with creasing to front bottom edge of wraps and sunning to spine; corners are lightly bumped; first few pages have mild discoloration but leaves are otherwise clean and binding tight; fore edge has teeny dampstains. Seller Inventory # 103344