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Pattern Recognition
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Pattern Recognition : Concepts, Methods and Applications

Softcover reprint of the original 1st ed. 2001

Book Details

Format Paperback / Softback
ISBN-10 3642626777
ISBN-13 9783642626777
Edition Softcover reprint of the original 1st ed. 2001
Publisher Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Country of Manufacture DE
Country of Publication GB
Publication Date Dec 5th, 2012
Print length 318 Pages
Weight 532 grams
Dimensions 15.70 x 23.30 x 2.40 cms
Ksh 8,100.00
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Pattern recognition currently comprises a vast body of methods supporting the development of numerous applications in many different areas of activity.
Pattern recognition currently comprises a vast body of methods supporting the development of numerous applications in many different areas of activity. The generally recognized relevance of pattern recognition methods and techniques lies, for the most part, in the general trend of "intelligent" task emulation, which has definitely pervaded our daily life. Robot assisted manufacture, medical diagnostic systems, forecast of economic variables, exploration of Earth's resources, and analysis of satellite data are just a few examples of activity fields where this trend applies. The pervasiveness of pattern recognition has boosted the number of task­ specific methodologies and enriched the number of links with other disciplines. As counterbalance to this dispersive tendency there have been, more recently, new theoretical developments that are bridging together many of the classical pattern recognition methods and presenting a new perspective of their links and inner workings. This book has its origin in an introductory course on pattern recognition taught at the Electrical and Computer Engineering Department, Oporto University. From the initial core of this course, the book grew with the intent of presenting a comprehensive and articulated view of pattern recognition methods combined with the intent of clarifying practical issues with the aid of examples and applications to real-life data. The book is primarily addressed to undergraduate and graduate students attending pattern recognition courses of engineering and computer science curricula.

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