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Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering [Paperback]

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  • Category: Books (Computers)
  • Author:  Angstenberger, Larisa
  • Author:  Angstenberger, Larisa
  • ISBN-10:  9048157757
  • ISBN-10:  9048157757
  • ISBN-13:  9789048157754
  • ISBN-13:  9789048157754
  • Publisher:  Springer
  • Publisher:  Springer
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Feb-2010
  • Pub Date:  01-Feb-2010
  • SKU:  9048157757-11-SPRI
  • SKU:  9048157757-11-SPRI
  • Item ID: 100960773
  • List Price: $109.99
  • Seller: ShopSpell
  • Ships in: 5 business days
  • Transit time: Up to 5 business days
  • Delivery by: Nov 25 to Nov 27
  • Notes: Brand New Book. Order Now.

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.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.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 Rel3

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