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Synopsis
This book introduces the reader to basic concepts and techniques in the field of fuzzy sets and gives a vast and up-to-date account of the literature. It distinguishes itself from most other works in this field in that it does not treat applications but rather provides a good theoretical foundation for applying fuzzy set theory.
The main topics which are treated are: basic set theory, basic lattice theory, operations on fuzzy sets, t-norms and t-conorms, special types of fuzzy sets, fuzzy relations, functions working on fuzzy sets, fuzzy real numbers (both probabilistic and non-probabilistic), basic classical logic and fundamentals concerning fuzzy logic.
Audience: This volume will be of interest to researchers working in the areas of engineering, data analysis, control theory, pattern recognition, neural networks, clustering, expert systems, information retrieval, operations research, decision making, image and signal processing, and who require more information on the set-theoretical basics on which fuzzy set theory is founded.
Booknews
Rather than mathematicians, this introductory treatment is geared toward researchers in engineering, data analysis, control theory, pattern recognition, neural networks, clustering, expert systems, information retrieval, operations research, decision making, and image and signal processing. Topics include elementary set theory, fuzzy sets, t-Norms, t-Conorms and Negations, special types of fuzzy sets, fuzzy real numbers, and fuzzy logic. Annotation c. Book News, Inc., Portland, OR (booknews.com)