Thursday, June 9, 2011

Pattern Recognition

Pattern Recognition
Author: Sergios Theodoridis
Edition: 4
Binding: Hardcover
ISBN: 1597492728



Pattern Recognition, Fourth Edition


This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. Download Pattern Recognition, Fourth Edition from rapidshare, mediafire, 4shared. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback.Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques Many more diagrams included--now in two color--to provide greater insight through visual presentation Matlab code of Search and find a lot of engineering books in many category availabe for free download.

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Download Pattern Recognition


Download Pattern Recognition engineering books for free. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques Many more diagrams included--now in two color--to provide greater insight through visual presentation Matlab code of

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Introduction to Pattern Recognition: A Matlab Approach


An accompanying manual to Theodoridis/Koutroumbas, Pattern Recognition, that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in ima

Pattern Classification (Pt.1)


The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learnin

Pattern Recognition and Machine Learning (Information Science and Statistics)


This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models

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