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Pattern Recognition,New
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This book considers classical and current theory and practice, of supervised, unsupervised and semisupervised 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 uptodate, selfcontained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semisupervised 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 includednow in two colorto 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 nonlinear dimensionality reduction techniques, relevance feedback, semisupervised 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 reallife data sets in imaging, and audio recognition. The companion book will be available separately or at a special packaged price (ISBN: 9780123744869). Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques Many more diagrams includednow in two colorto 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 reallife data sets in imaging and audio recognition. The companion book is available separately or at a special packaged price (Book ISBN: 9780123744869. Package ISBN: 9780123744913) Latest hot topics included to further the reference value of the text including nonlinear dimensionality reduction techniques, relevance feedback, semisupervised 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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