Dynamic fuzzy pattern recognition with applications to finance and engineering
Author(s)
Bibliographic Information
Dynamic fuzzy pattern recognition with applications to finance and engineering
（International series in intelligent technologies, 17）
Kluwer Academic, c2001
Available at 6 libraries
Note
Includes bibliographical references and index
Description and Table of Contents
Description
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.
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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