Fuzzy Learning and Applications

AvMarco Russo

Inbunden, Engelska, 2000

Del i serien International Series on Computational Intelligence

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Beskrivning

With low computational complexity and relatively short development time, Fuzzy Logic is an indispensable tool for engineering applications. The field is growing at an unprecedented rate, and there is a need for a book that describes essential tools, applications, examples, and perspectives in the field of fuzzy learning. The editors of Fuzzy Learning and Applications fill this need, providing an essential book for researchers, scientists, and engineers alike.Organized into four parts, this book starts with the simplest learning method and gradually arrives at the most complex. First, it summarizes all the symbols and formulae used in the succeeding chapters and presents a historical overview of fuzzy learning. Next, it deals with current techniques, ranging from deterministic to hybrid methods. It then illustrates the enormous number of possibilities offered by fuzzy learning. Finally, it covers hardware dedicated to fuzzy learning, from digital to analog designs and implementations. With Fuzzy Learning and Applications, readers will discover the enormous possibilities fuzzy learning offers.

Produktinformation

Utgivningsdatum:2000-12-13
Mått:156 x 234 x undefined mm
Vikt:690 g
Format:Inbunden
Språk:Engelska
Serie:International Series on Computational Intelligence
Antal sidor:404
Förlag:Taylor & Francis Inc
ISBN:9780849322693

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Mer om författaren

Russo, Marco; Jain, Lakhmi C.

Recensioner i media

"This book would be an excellent resource for graduate students and advanced researchers in two ways: it would enable them to learn about some of the advanced research and applications being carried out, and would provide them with a variety of ideas for further research and applications."-R. Bharath, CHOICE, September 2001

Innehållsförteckning

Evolutionary Fuzzy Learning, M. RussoA Stored-Programmable Mixed-Signal Fuzzy Controller Chip with Supervised Learning Capabilities, F. Vidal-Verdú, R. Navas, M. Delgado-Restituto, and A. Rodríguez-VázquezFuzzy Modeling in a Multi-Agent Framework for Learning in Autonomous Systems, Juan A. Botía, Humberto Martínez Barberá, and Antonio F. Gómez SkármetaLearning Techniques for Supervised Fuzzy Classifiers, F. Masulli and A. SperdutiMultistage Fuzzy Control, Z.M. Yeh and H.P. ChenLearning Fuzzy Systems, A. LoftiApplication of Fuzzy Modeling to Analysis of Rowing Boat Speed, K. Tachibana, T. Furuhashi, M. Shimoda, Y. Kawakami, and T. FukunagaA Novel Fuzzy Approach to Hopfield Coefficients Determination, S. Cavalieri and M. RussoFuzzy Control of a CD Player Focusing System, L. Fortuna, G. Muscato, R. Caponetto, and M.G. XibiliaA Neuro-Fuzzy Scheduler for a Multi-Media Web Server, Z. Ali, A. Ghafoor, and C.S.G. LeeA Neuro-Fuzzy System Based on Logical Interpretation of If-Then Rules, J. Leski and N. Henzel