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OverviewFlexible Neuro-Fuzzy Systems is the first professional literature about the new class of powerful, flexible fuzzy systems. The author incorporates various flexibility parameters to the construction of neuro-fuzzy systems. This approach dramatically improves their performance, allowing the systems to perfectly represent the pattern encoded in data. Flexible Neuro-Fuzzy Systems is the only book that proposes a flexible approach to fuzzy modeling and fills the gap in existing literature. This book introduces new fuzzy systems which outperform previous approaches to system modeling and classification, and has the following features: -Provides a framework for unification, construction and development of neuro-fuzzy systems; -Presents complete algorithms in a systematic and structured fashion, facilitating understanding and implementation, -Covers not only advanced topics but also fundamentals of fuzzy sets, -Includes problems and exercises following each chapter, -Illustrates the results on a wide variety of simulations, -Provides tools for possible applications in business and economics, medicine and bioengineering, automatic control, robotics and civil engineering. Full Product DetailsAuthor: Leszek RutkowskiPublisher: Springer-Verlag New York Inc. Imprint: Springer-Verlag New York Inc. Edition: Softcover reprint of the original 1st ed. 2004 Volume: 771 Dimensions: Width: 15.50cm , Height: 1.60cm , Length: 23.50cm Weight: 0.456kg ISBN: 9781475779325ISBN 10: 1475779321 Pages: 279 Publication Date: 23 April 2013 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsElements of the Theory of Fuzzy Sets.- Fuzzy Inference Systems.- Flexibility in Fuzzy Systems.- Flexible Or-Type Neuro-Fuzzy Systems.- Flexible Compromise and-Type Neuro-Fuzzy Systems.- Flexible Mamdani-Type Neuro-Fuzzy Systems.- Flexible Logical-Type Neuro-Fuzzy Systems.- Performance Comparison of Neuro-Fuzzy Systems.ReviewsFrom the reviews: This research monograph offers a very detailed insight into ... flexible neurofuzzy architectures. ... The author systematically guides the reader through the essence of the neurofuzzy systems. ... Careful attention to details along with well-organized and systematic derivations of all learning formulas are the important features of the book. The wealth of experimental material and thorough comparative analysis is another strength of the book. The list of references is very much updated ... . Overall, the book is worth studying. (Witold Pedrycz, Zentralblatt MATH, Vol. 1080, 2006) It is fair to say that the work presented in this book moves the whole area of modeling by neuro-fuzzy systems to a higher level. ... a great resource for researchers in this area, who have a fairly strong background in both fuzzy systems and artificial neural networks. It is also an excellent textbook for advanced graduate students in engineering, systems science, computer science, information science, and perhaps some other areas, who are interested in neuro-fuzzy systems and, more generally, in applications of fuzzy mathematics. (George J. Klir, International Journal of General Systems, Vol. 34 (3), 2005) "From the reviews: ""This research monograph offers a very detailed insight into … flexible neurofuzzy architectures. … The author systematically guides the reader through the essence of the neurofuzzy systems. … Careful attention to details along with well-organized and systematic derivations of all learning formulas are the important features of the book. The wealth of experimental material and thorough comparative analysis is another strength of the book. The list of references is very much updated … . Overall, the book is worth studying."" (Witold Pedrycz, Zentralblatt MATH, Vol. 1080, 2006) ""It is fair to say that the work presented in this book moves the whole area of modeling by neuro-fuzzy systems to a higher level. … a great resource for researchers in this area, who have a fairly strong background in both fuzzy systems and artificial neural networks. It is also an excellent textbook for advanced graduate students in engineering, systems science, computer science, information science, and perhaps some other areas, who are interested in neuro-fuzzy systems and, more generally, in applications of fuzzy mathematics."" (George J. Klir, International Journal of General Systems, Vol. 34 (3), 2005)" Author InformationTab Content 6Author Website:Countries AvailableAll regions |