William S. Meisel (Eds.)9780124888500, 0-12-488850-X
Table of contents :
Content:
Edited by
Page iii
Copyright page
Page iv
Dedication
Page v
Preface
Pages xi-xii
Chapter I Basic Concepts and Methods in Mathematical Pattern Recognition
Pages 1-37
Chapter II The Statistical Formulation and Parametric Methods
Pages 38-46
Chapter III Introduction to Optimization Techniques
Pages 47-54
Chapter IV Linear Discriminant Functions and Extensions
Pages 55-84
Chapter V Indirect Approximation of Probability Densities
Pages 85-97
Chapter VI Direct Construction of Probability Densities: Potential Functions (Parzen Estimators)
Pages 98-119
Chapter VII Piecewise Linear Discriminant Functions
Pages 120-137
Chapter VIII Cluster Analysis and Unsupervised Learning
Pages 138-161
Chapter IX Feature Selection
Pages 162-213
Chapter X Special Topics
Pages 214-227
Appendix A A Set of Orthonormal Polynomials
Pages 228-229
Appendix B Efficient Representation and Approximation of Multivariate Functions
Pages 230-246
Index
Pages 247-250
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