A Learner’s Guide to Fuzzy Logic Systems, Second Edition
Autor K Sundareswaranen Limba Engleză Hardback – 25 iun 2019
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Specificații
ISBN-13: 9780367254438
ISBN-10: 0367254433
Pagini: 126
Ilustrații: 14 Tables, black and white; 25 Illustrations, black and white
Dimensiuni: 138 x 216 x 8 mm
Greutate: 0.27 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
ISBN-10: 0367254433
Pagini: 126
Ilustrații: 14 Tables, black and white; 25 Illustrations, black and white
Dimensiuni: 138 x 216 x 8 mm
Greutate: 0.27 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Public țintă
Postgraduate and UndergraduateCuprins
1. Unravelling Uncertainty Through Simple Examples. 2. Fuzzy Sets. 3. Fuzzy Reasoning. 4. Design Aspects of Fuzzy Systems.
Notă biografică
Dr. K. Sundareswaran, obtained his M.Tech. (Hons.) in power electronics from the university of Calicut, and Ph.D. from Bharathidasan University, Tiruchirappalli. He is currently working as Professor in the department of Electrical and electronics Engineering, National Institute of Technology, Tiruchirappalli.
From 2005 to 2006, he was a Professor with the Department of Electrical Engineering, National Institute of Technology, Calicut, Kerala, India. He is currently a Professor with the Department of Electrical and Electronics Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India. His research interests include power electronics, renewable energy systems, and biologically inspired optimization techniques.
From 2005 to 2006, he was a Professor with the Department of Electrical Engineering, National Institute of Technology, Calicut, Kerala, India. He is currently a Professor with the Department of Electrical and Electronics Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India. His research interests include power electronics, renewable energy systems, and biologically inspired optimization techniques.
Descriere
This book presents a very introductory coverage of the topic of fuzzy logic, including a few basic principles from an interdisciplinary perspective. It includes concept of evolving a fuzzy set and fuzzy set operations, fuzzification rule base design and defuzzification and simple guidelines for fuzzy sets design and selected applications.