دانلود کتاب Pattern Recognition

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Content:
Preface, Pages xv-xvi
Chapter 1 - Introduction, Pages 1-11
Chapter 2 - Classifiers Based on Bayes Decision Theory, Pages 13-67
Chapter 3 - Linear Classifiers, Pages 69-120
Chepter 4 - Nonlinear Classifiers, Pages 121-211
Chapter 5 - Feature Selection, Pages 213-262
Chapter 6 - Feature Generation I: Linear Transforms, Pages 263-326
Chapter 7 - Feature Generation II, Pages 327-396
Chapter 8 - Template Matching, Pages 397-426
Chapter 9 - Context-Dependent Classification, Pages 427-469
Chapter 10 - System Evaluation, Pages 471-481
Chapter 11 - Clustering: Basic Concepts, Pages 483-516
Chapter 12 - Clustering Algorithms I: Sequential Algorithms, Pages 517-540
Chapter 13 - Clustering Algorithms II: Hierarchical Algorithms, Pages 541-587
Chapter 14 - Clustering Algorithms III: Schemes Based on Function Optimization, Pages 589-651
Chapter 15 - Clustering Algorithms IV, Pages 653-731
Chapter 16 - Cluster Validity, Pages 733-783
Appendix A - Hints from Probability and Statistics, Pages 785-796
Appendix B - Linear Algebra Basics, Pages 797-799
Appendix C - Cost Function Optimization, Pages 801-818
Appendix D - Basic Definitions from Linear Systems Theory, Pages 819-822
Index, Pages 823-837