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esigned primarily as a text for senior undergraduate students of Computer Science and Engineering, and postgraduate students of Mathematics and Applied Mathematics, this compact book describes the theoretical aspects of fuzzy set theory and fuzzy logic. Based on his many years of experience, Professor Rajjan Shinghal gives a succinct analysis of the procedures for fuzzy sets complementation, intersection, and union. He also explains clearly how arithmetic operations are carried out on approximate numbers, how fuzzy sets are used for reasoning, and how they are employed for unsupervised learning. Finally, the book shows how fuzzy sets are utilized in applications such as logic control, databases, information retrieval, ordering of objects, and satisfying multiple goals. Besides students, professionals working in research organizations should find the book quite useful. About the Author Rajjan Shinghal (PhD), formerly Professor of Computer Science, Concordia University, Montreal, Canada, has over 30 years of teaching and research experience. He has published several papers in reputed journals such as IEEE Transactions on Medical Imaging, IEEE Transactions on Systems, Man, and Cybernetics, IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Expert Systems, and International Journal of Pattern Recognition and Artificial Intelligence. Besides, he has presented several research papers in various inter-national conferences and workshops. In addition, Professor Shinghal has authored two books, one on Pattern Recognition and the other on Formal Concepts in Artificial Intelligence. Table of Contents Preface Chapter 1 An Overview of Crisp Sets Chapter 2 Basics of Fuzzy Sets Chapter 3 Developing Membership Functions Chapter 4 Complement of a Fuzzy Set Chapter 5 Intersection and Union of Fuzzy Sets Chapter 6 Fuzzy Arithmetic with Extension Principle Chapter 7 Fuzzy Arithmetic with Interval Analysis Chapter 8 Fuzzy Relations for Mapping of Fuzzy Sets Chapter 9 Defuzzification Chapter 10 Approximate Reasoning: Modus Ponens Chapter 11 Approximate Reasoning: Modus Tollens Chapter 12 Fuzzy Clustering Chapter 13 Fuzzy Logic Applications Bibliography Index