Fuzzy Neural Intelligent Systems : Mathematical Foundation and the Applications in Engineering
Book Details
Format
Hardback or Cased Book
ISBN-10
0849323606
ISBN-13
9780849323607
Publisher
Taylor & Francis Inc
Imprint
CRC Press Inc
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Sep 21st, 2000
Print length
392 Pages
Weight
680 grams
Product Classification:
Neural networks & fuzzy systems
Ksh 22,500.00
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Develops a mathematical basis for fuzzy neural networks. This work features: fundamental concepts and theories for fuzzy systems and neural networks; foundation for fuzzy neural networks and important related topics; and, case examples for neuro-fuzzy systems, fuzzy systems, neural network systems, and fuzzy-neural systems.
Although fuzzy systems and neural networks are central to the field of soft computing, most research work has focused on the development of the theories, algorithms, and designs of systems for specific applications. There has been little theoretical support for fuzzy neural systems, especially their mathematical foundations.
Fuzzy Neural Intelligent Systems fills this gap. It develops a mathematical basis for fuzzy neural networks, offers a better way of combining fuzzy logic systems with neural networks, and explores some of their engineering applications. Dividing their focus into three main areas of interest, the authors give a systematic, comprehensive treatment of the relevant concepts and modern practical applications:
Fundamental concepts and theories for fuzzy systems and neural networks.
Foundation for fuzzy neural networks and important related topics
Case examples for neuro-fuzzy systems, fuzzy systems, neural network systems, and fuzzy-neural systems
Suitable for self-study, as a reference, and ideal as a textbook, Fuzzy Neural Intelligent Systems is accessible to students with a basic background in linear algebra and engineering mathematics. Mastering the material in this textbook will prepare students to better understand, design, and implement fuzzy neural systems, develop new applications, and further advance the field.
Fuzzy Neural Intelligent Systems fills this gap. It develops a mathematical basis for fuzzy neural networks, offers a better way of combining fuzzy logic systems with neural networks, and explores some of their engineering applications. Dividing their focus into three main areas of interest, the authors give a systematic, comprehensive treatment of the relevant concepts and modern practical applications:
Suitable for self-study, as a reference, and ideal as a textbook, Fuzzy Neural Intelligent Systems is accessible to students with a basic background in linear algebra and engineering mathematics. Mastering the material in this textbook will prepare students to better understand, design, and implement fuzzy neural systems, develop new applications, and further advance the field.
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