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Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering / Edition 1
     

Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering / Edition 1

by Larisa Angstenberger
 

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ISBN-10: 9048157757

ISBN-13: 9789048157754

Pub. Date: 12/06/2010

Publisher: Springer Netherlands

Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering focuses on fuzzy clustering methods which have proven to be very powerful in pattern recognition and considers the entire process of dynamic pattern recognition. This book sets a general framework for Dynamic Pattern Recognition, describing in detail the monitoring process using fuzzy

Overview

Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering focuses on fuzzy clustering methods which have proven to be very powerful in pattern recognition and considers the entire process of dynamic pattern recognition. This book sets a general framework for Dynamic Pattern Recognition, describing in detail the monitoring process using fuzzy tools and the adaptation process in which the classifiers have to be adapted, using the observations of the dynamic process. It then focuses on the problem of a changing cluster structure (new clusters, merging of clusters, splitting of clusters and the detection of gradual changes in the cluster structure). Finally, the book integrates these parts into a complete algorithm for dynamic fuzzy classifier design and classification.

Product Details

ISBN-13:
9789048157754
Publisher:
Springer Netherlands
Publication date:
12/06/2010
Series:
International Series in Intelligent Technologies , #17
Edition description:
Softcover reprint of hardcover 1st ed. 2001
Pages:
288
Product dimensions:
6.10(w) x 9.25(h) x 0.03(d)

Related Subjects

Table of Contents

Foreword. Acknowledgements. 1. Introduction. 2. General Framework of Dynamic Pattern Recognition. 3. Stages of the Dynamic Pattern Recognition Process. 4. Dynamic Fuzzy Classifier Design with Point-Prototype Based Clustering Algorithms. 5. Similarity Concepts for Dynamic Objects in Pattern Recognition. 6. Applications of Dynamic Pattern Recognition Methods. 7. Conclusions. References.

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