Pattern Classification

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John Wiley & Sons, Nov 9, 2012 - Technology & Engineering - 680 pages
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The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

 

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Contents

1 INTRODUCTION
1
2 BAYESIAN DECISION THEORY
20
3 MAXIMUMLIKELIHOOD AND BAYESIAN PARAMETER ESTIMATION
84
4 NONPARAMETRIC TECHNIQUES
161
5 LINEAR DISCRIMINANT FUNCTIONS
215
6 MULTILAYER NEURAL NETWORKS
282
7 STOCHASTIC METHODS
350
8 NONMETRIC METHODS
394
9 ALGORITHMINDEPENDENT MACHINE LEARNING
453
10 UNSUPERVISED LEARNING AND CLUSTERING
517
A MATHEMATICAL FOUNDATIONS
601
INDEX
637
Copyright

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About the author (2012)

RICHARD O. DUDA, PhD, is Professor in the Electrical Engineering Department at San Jose State University, San Jose, California.

PETER E. HART, PhD, is Chief Executive Officer and President of Ricoh Innovations, Inc. in Menlo Park, California.

DAVID G. STORK, PhD, is Chief Scientist, also at Ricoh Innovations, Inc.

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