Abstract

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 topicsCase examples for neuro-fuzzy systems, fuzzy systems, neural network systems, and fuzzy-neural systemsSuitable 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.

Keywords:
Artificial intelligence Computer science Neuro-fuzzy Fuzzy logic Artificial neural network Neural system Fuzzy control system Psychology Neuroscience

Metrics

6
Cited By
0.25
FWCI (Field Weighted Citation Impact)
0
Refs
0.70
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Fuzzy Logic and Control Systems
Physical Sciences →  Computer Science →  Artificial Intelligence
Neural Networks and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence

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