Pattern Recognition - Hardcover

Koutroumbas, Konstantinos; Theodoridis, Sergios

Hardcover

ISBN 10: 1597492728 ISBN 13: 9781597492720

Publisher: Academic Press, 2008

Synopsis

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).

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: 9780123744913)

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.

About this title

Book Description:

A classic that offers comprehensive coverage with a balance between theory and practice.

From the Back Cover:

Pattern recognition is becoming increasingly important in the age of automation and information handling and retrieval.
This book provides the most comprehensive treatment available of pattern recognition, from an engineering perspective. Developed through more than ten years of teaching experience, Pattern Recognition is appropriate for both advanced engineering students and practicing engineers.

Coverage includes:
· Feature generation, including features based on Wavelet Transforms and Fractals.
· Feature selection techniques.
· Design of linear and non linear classifiers, including Bayesian, Multilayer Perceptrons, and RBF networks
. Context-dependent classification, including Dynamic Programming and Hidden Markov Modeling techniques
. Classical approaches, as well as more recent developments in clustering algorithms, such as fuzzy, possibilistic, morphological, genetic, and annealing techniques
. Coverage of numerous, diverse applications, including Image Analysis, Character Recognition, Medical Diagnosis, Speech Recognition, and Channel Equalization
. Numerous computer simulation examples, supporting the methods given in the book, available via the Webb.

About this edition

• Publisher: Academic Press
• Publication date: 2008
• ISBN 10: 1597492728
• ISBN 13: 9781597492720
• Binding: Hardcover
• Edition number: 4
• Number of pages: 984