Data Clustering
In the previous chapters, when introducing the idea of similarity as a distance between feature vectors, we often computed this distance relative to a prototype pattern. We have also implicitly assumed that the shape of the class distributions in the feat
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Springer-Verlag Berlin Heidelberg GmbH
J. P. Marques de Sa
Pattern Recognition Concepts, Methods and Applications
With 197 Figures
,
Springer
Prof. Joaquim P. Marques de Sa Universidade do Porto Faculdade de Engenharia Rua Dr. Roberto Frias 4200-465 Porto Portugal e-mail: [email protected]
Cip data applied for Die Deutsche Bibliothek - Cip-Einheitsaufnahme Sa, Joaquim P. Marques de: Pattern recognition : concepts, methods and applications I J. P. Marques de Sa. - Berlin; Heidelberg ; New York; Barcelona; Hong Kong ; London ; Milan ; Paris; Singapore; Tokyo: Springer, 2001 ISBN 978-3-642-62677-7 ISBN978-3-642-56651-6 (eBook) DOI 10.1007/978-3-642-56651-6
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2001
Originally published by Springer-Verlag Berlin Heidelberg New York in 2001 The use of general descriptive names, registered names trademarks, etc. in this publicat ion does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Typesetting: data delivered by author Cover design: de'blik, Berlin Printed on acid free paper SPIN: 10844202
62/3020/M - 5 4 3 2 1 O
To my wife Wiesje and our son Carlos, lovingly.
Preface
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 taskspecific 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
