Introduction to Statistical Pattern Recognition
eBook - ePub

Introduction to Statistical Pattern Recognition

  1. 592 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Introduction to Statistical Pattern Recognition

About this book

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.

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Yes, you can access Introduction to Statistical Pattern Recognition by Keinosuke Fukunaga in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Vision & Pattern Recognition. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. In Side Front Cover
  5. Copyright
  6. Dedication
  7. Preface
  8. Acknowledgments
  9. Chapter 1: INTRODUCTION
  10. Chapter 2: RANDOM VECTORS AND THEIR PROPERTIES
  11. Chapter 3: HYPOTHESIS TESTING
  12. Chapter 4: PARAMETRIC CLASSIFIERS
  13. Chapter 5: PARAMETER ESTIMATION
  14. Chapter 6: NONPARAMETRIC DENSITY ESTIMATION
  15. Chapter 7: NONPARAMETRIC CLASSIFICATION AND ERROR ESTIMATION
  16. Chapter 8: SUCCESSIVE PARAMETER ESTIMATION
  17. Chapter 9: FEATURE EXTRACTION AND LINEAR MAPPING FOR SIGNAL REPRESENTATION
  18. Chapter 10: FEATURE EXTRACTION AND LINEAR MAPPING FOR CLASSIFICATION
  19. Chapter 11: CLUSTERING
  20. Appendix A: DERIVATIVES OF MATRICES
  21. Appendix B: MATHEMATICAL FORMULAS
  22. Appendix C: NORMAL ERROR TABLE
  23. Appendix D: GAMMA FUNCTION TABLE
  24. INDEX