An Introduction to Computing with Fuzzy Sets - Pedrycz, Witold

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Résumé :
This book provides concise yet thorough coverage of the fundamentals and technology of fuzzy sets. Readers will find a lucid and systematic introduction to the essential concepts of fuzzy set-based information granules, their processing and detailed algorithms. Timely topics and recent advances in fuzzy modeling and its principles, neurocomputing, fuzzy set estimation, granulation?degranulation, and fuzzy sets of higher type and order are discussed. In turn, a wealth of examples, case studies, problems and motivating arguments, spread throughout the text and linked with various areas of artificial intelligence, will help readers acquire a solid working knowledge. Given the book?s well-balanced combination of the theory and applied facets of fuzzy sets, it will appeal to a broad readership in both academe and industry. It is also ideally suited as a textbook for graduate and undergraduate students in science, engineering, and operations research.

Biographie:
Bruno Apolloni is Full Professor in Computer Science in the University of Milano, Italy. His main research interests are at the frontier area between probability and mathematical statistics and computer science, with special interest to pattern recognition and multivariate data analysis, probabilistic analysis of algorithms, subsymbolic and symbolic learning processes, and fuzzy systems. Witold Pedrycz is Professor and Canada Research Chair (CRC) in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences. His dominant research is in Computational Intelligence, fuzzy modeling, knowledge discovery and data mining, pattern recognition, and knowledge-based neural networks. Dario Malchiodi is Assistant Professor in the Computer Science Department, University of Milano, Italy. His research activities concern the treatment of uncertain information and related aspects of mathematical statistics and artificial intelligence, including applications to machine learning and relevance learning. Simone Bassis is an assistant professor in the Department of Computer Science, University of Milano, Italy. His main research activities concern the inference of spatial and temporal processes, including linear and nonlinear statistical regression, fractal processes identification, and evolutionary dynamics....

Sommaire:
TOC is available in MS