Pattern Recognition with Fuzzy Objective Function Algorithms

Language: English

Published by Springer, 2012

1475704526 / 9781475704525

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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Druck auf Anfrage Neuware - Printed after ordering - 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.…

Seller Inventory # 9781475704525

Title
Pattern Recognition with Fuzzy Objective Function Algorithms
Author
James C. Bezdek
Publisher
Springer
Publication year
2012
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
1475704526
ISBN 13
9781475704525
Item weight
404 grams
Dimensions
229x152x16 mm

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