| 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 |
| Chapter 5 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 Analysis |
| 7.3 Voting kNN Procedure - Finite Sample Analysis |
| 7.4 Error Estimation |
| 7.5 Miscellaneous Topics in the kNN Approach |
| Computer Projects |
| Problems |
| References |
| Chapter 8 Successive Parameter Estimation |
| 8.1 Successive Adjustment of a Linear Classifier |
| 8.2 Stochastic Approximation |
| 8.3 Successive Bayes Estimation |
| Computer Projects |
| Problems |
| References |
| Chapter 9 Feature Extraction and Linear Mapping for Signal Representation |
| 9.1 The Discrete Karhunen-Loéve Expansion |
| 9.2 The Karhunen-Loéve Expansion for Random Processes |
| 9.3 Estimation of Eigenvalues and Eigenvectors |
| Computer Projects |
| Problems |
| References |
| Chapter 10 Feature Extraction and Linear Mapping for Classification |
| 10.1 General Problem Formulation |
| 10.2 Discriminant Analysis |
| 10.3 Generalized Criteria |
| 10.4 Nonparametric Discriminant Analysis |
| 10.5 Sequential Selection of Quadratic Features |
| 10.6 Feature Subset Selection |
| Computer Projects |
| Problems |
| References |
| Chapter 11 Clustering |
| 11.1 Parametric Clustering |
| 11.2 Nonparametric Clustering |
| 11.3 Selection of Representatives |
| Computer Projects |
| Problems |
| References |
| Appendix A Derivatives of Matrices |
| Appendix B Mathematical Formulas |
| Appendix C Normal Error Table |
| Appendix D Gamma Function Table |
| Index |
