Advanced Applications in Pattern Recognition

Pattern Recognition with Fuzzy Objective Function Algorithms

Authors: Bezdek, James C.

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About this book

The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973, however, when the appearance of the work by Dunn and Bezdek on the Fuzzy ISODATA (or fuzzy c-means) algorithms became a landmark in the theory of cluster analysis, that the relevance of the theory of fuzzy sets to cluster analysis and pattern recognition became clearly established. Since then, the theory of fuzzy clustering has developed rapidly and fruitfully, with the author of the present monograph contributing a major share of what we know today. In their seminal work, Bezdek and Dunn have introduced the basic idea of determining the fuzzy clusters by minimizing an appropriately defined functional, and have derived iterative algorithms for computing the membership functions for the clusters in question. The important issue of convergence of such algorithms has become much better understood as a result of recent work which is described in the monograph.

Table of contents (6 chapters)

Buy this book

eBook $89.00
price for USA (gross)
  • ISBN 978-1-4757-0450-1
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $119.00
price for USA
valid through November 5, 2017
  • ISBN 978-1-4757-0452-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Pattern Recognition with Fuzzy Objective Function Algorithms
Authors
Series Title
Advanced Applications in Pattern Recognition
Copyright
1981
Publisher
Springer US
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-1-4757-0450-1
DOI
10.1007/978-1-4757-0450-1
Softcover ISBN
978-1-4757-0452-5
Edition Number
1
Number of Pages
272
Topics