Pattern recognition

Sergios Theodoridis and Konstantinos Koutroumbas

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. 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 the most common methods are given at the end of each chapter. * More Matlab code is available, together with an accompanying manual, via this site * Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms. * An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary, and solved examples including real-life data sets in imaging, and audio recognition. The companion book will be available separately or at a special packaged price (ISBN: 9780123744869). Combines classical topics (supervised learning) with the most modern topics (unsupervised and semi-supervised learning) in pattern recognition today, making it a complete reference for researchers and R&D engineers and graduate students. New to this edition: * 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 the most common methods are given at the end of each chapter * An accompanying book with 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 imaging and audio recognition. The companion book is available separately or at a special packaged price (Book ISBN: 9780123744869. Package ISBN: 9780123744869) * Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms * Solutions manual, powerpoint slides, and additional resources are available to faculty using the text for their course. Register at www.textbooks.elsevier.com and search on "Theodoridis" to access resources for instructor.

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この本の情報

書名 Pattern recognition
著作者等 Theodoridis, Sergios
Koutroumbas Konstantinos
出版元 Academic Press, an imprint of Elsevier
刊行年月 c2009
版表示 4th ed
ページ数 xvii, 961 p.
大きさ 24 cm
ISBN 9781597492720
NCID BA87671814
※クリックでCiNii Booksを表示
言語 英語
出版国 アメリカ合衆国
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