eBook - PDF
Introduction to Pattern Recognition
Statistical, Structural, Neural and Fuzzy Logic Approaches
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- 344 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Introduction to Pattern Recognition
Statistical, Structural, Neural and Fuzzy Logic Approaches
Book details
Table of contents
Citations
About This Book
This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications. In addition to statistical and structural approaches, novel topics such as fuzzy pattern recognition and pattern recognition via neural networks are also reviewed. Each topic is followed by several examples solved in detail. The only prerequisites for using this book are a one-semester course in discrete mathematics and a knowledge of the basic preliminaries of calculus, linear algebra and probability theory.
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Yes, you can access Introduction to Pattern Recognition by Menahem Friedman, Abraham Kandel;;; 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.
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Table of contents
- Contents
- PREFACE
- 1 INTRODUCTION
- 2 DECISION FUNCTIONS
- 3 CLASSIFICATION BY DISTANCE FUNCTIONS AND CLUSTERING
- 4 CLASSIFICATION USING STATISTICAL APPROACH
- 5 FEATURE SELECTION
- 6 FUZZY CLASSIFICATION AND PATTERN RECOGNITION
- 7 SYNTACTIC PATTERN RECOGNITION
- 8 NEURAL NETS AND PATTERN CLASSIFICATION
- APPENDIX
- Index