Introduction to Statistical Pattern Recognition

2nd Edition

Authors: Keinosuke Fukunaga
Hardcover ISBN: 9780122698514
eBook ISBN: 9780080478654
Imprint: Academic Press
Published Date: 28th September 1990
Page Count: 592
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Description

This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.

Table of Contents


Preface


Acknowledgments


Chapter 1 Introduction


1.1 Formulation of Pattern Recognition Problems


1.2 Process of Classifier Design


Notation


References


Chapter 2 Random Vectors and Their Properties


2.1 Random Vectors and Their Distributions


2.2 Estimation of Parameters


2.3 Linear Transformation


2.4 Various Properties of Eigenvalues and Eigenvectors


Computer Projects


Problems


References


Chapter 3 Hypothesis Testing


3.1 Hypothesis Tests for Two Classes


3.2 Other Hypothesis Tests


3.3 Error Probability in Hypothesis Testing


3.4 Upper Bounds on the Bayes Error


3.5 Sequential Hypothesis Testing


Computer Projects


Problems


References


Chapter 4 Parametric Classifiers


4.1 The Bayes Linear Classifier


4.2 Linear Classifier Design


4.3 Quadratic Classifier Design


4.4 Other Classifiers


Computer Projects


Problems


References


Chapter5 Parameter Estimation


5.1 Effect of Sample Size in Estimation


5.2 Estimation of Classification Errors


5.3 Holdout, Leave-One-Out, and Resubstitution Methods


5.4 Bootstrap Methods


Computer Projects


Problems


References


Chapter 6 Nonparametric Density Estimation


6.1 Parzen Density Estimate


6.2 kNearest Neighbor Density Estimate


6.3 Expansion by Basis Functions


Computer Projects


Problems


References


Chapter 7 Nonparametric Classification and Error Estimation


7.1 General Discussion


7.2 Voting kNN Procedure — Asymptotic Analysi

Details

No. of pages:
592
Language:
English
Copyright:
© Academic Press 1990
Published:
Imprint:
Academic Press
eBook ISBN:
9780080478654
Hardcover ISBN:
9780122698514

About the Author

Keinosuke Fukunaga