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Fuzzy Learning and Applications
— —
Marco Russo Prof. Lakhmi C. Jain
Fuzzy Learning and Applications by Marco Russo at Abbey's Bookshop,

Fuzzy Learning and Applications

Marco Russo Prof. Lakhmi C. Jain


9780849322693

CRC Press Inc


Machine learning


Hardback

408 pages

$210.00
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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.

By:   Marco Russo, Prof. Lakhmi C. Jain
Imprint:   CRC Press Inc
Country of Publication:   United States
Volume:   19
Dimensions:   Height: 235mm,  Width: 156mm,  Spine: 24mm
Weight:   689g
ISBN:   9780849322693
ISBN 10:   0849322693
Series:   International Series on Computational Intelligence
Pages:   408
Publication Date:   December 2000
Audience:   College/higher education ,  Professional and scholarly ,  Professional & Vocational ,  A / AS level ,  Further / Higher Education
Format:   Hardback
Publisher's Status:   Active

Evolutionary Fuzzy Learning, M. Russo A Stored-Programmable Mixed-Signal Fuzzy Controller Chip with Supervised Learning Capabilities, F. Vidal-Verdu, R. Navas, M. Delgado-Restituto, and A. Rodriguez-Vazquez Fuzzy Modeling in a Multi-Agent Framework for Learning in Autonomous Systems, Juan A. Botia, Humberto Martinez Barbera, and Antonio F. Gomez Skarmeta Learning Techniques for Supervised Fuzzy Classifiers, F. Masulli and A. Sperduti Multistage Fuzzy Control, Z.M. Yeh and H.P. Chen Learning Fuzzy Systems, A. Lofti Application of Fuzzy Modeling to Analysis of Rowing Boat Speed, K. Tachibana, T. Furuhashi, M. Shimoda, Y. Kawakami, and T. Fukunaga A Novel Fuzzy Approach to Hopfield Coefficients Determination, S. Cavalieri and M. Russo Fuzzy Control of a CD Player Focusing System, L. Fortuna, G. Muscato, R. Caponetto, and M.G. Xibilia A Neuro-Fuzzy Scheduler for a Multi-Media Web Server, Z. Ali, A. Ghafoor, and C.S.G. Lee A Neuro-Fuzzy System Based on Logical Interpretation of If-Then Rules, J. Leski and N. Henzel

Russo\, Marco; Jain\, Lakhmi C.


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

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