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Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering

  • Authors
  • Larisa¬†Angstenberger

Part of the International Series in Intelligent Technologies book series (ISIT, volume 17)

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Larisa Angstenberger
    Pages 1-5
  3. Larisa Angstenberger
    Pages 7-36
  4. Larisa Angstenberger
    Pages 37-78
  5. Larisa Angstenberger
    Pages 199-263
  6. Larisa Angstenberger
    Pages 265-267
  7. Back Matter
    Pages 269-287

About this book

Introduction

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.

Keywords

algorithms classification cognition fuzzy knowledge pattern recognition

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-017-1312-2
  • Copyright Information Springer Science+Business Media B.V. 2001
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-5775-4
  • Online ISBN 978-94-017-1312-2
  • Series Print ISSN 1382-3434
  • Buy this book on publisher's site
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