Introduction to pattern recognition : statistical, structural, neural, and fuzzy logic approaches

Bibliographic Information

Introduction to pattern recognition : statistical, structural, neural, and fuzzy logic approaches

Menahem Friedman, Abraham Kandel

(Series in machine perception and artificial intelligence / editors, H. Bunke, P.S.P. Wang, vol. 32)

World scientific, 1999

Available at  / 10 libraries

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Note

Includes bibliographical references

Description and Table of Contents

Description

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.

Table of Contents

  • Decision functions
  • classification by distance functions and clustering
  • classification using statistical approach
  • feature selection
  • fuzzy classification and pattern recognition
  • syntactic pattern recognition
  • neural nets and pattern classification.

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Details

  • NCID
    BA41192653
  • ISBN
    • 9810233124
  • LCCN
    98032406
  • Country Code
    us
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    River Edge, NJ
  • Pages/Volumes
    329p.
  • Size
    26cm
  • Classification
  • Subject Headings
  • Parent Bibliography ID
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