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This textbook offers a unified engineering perspective on Neural Networks and Fuzzy Logic. The authors guide readers swiftly and succinctly through the intricate subjects of neural networks, fuzzy logic, and the mathematical modeling of Fuzzy Logic Control. The theory of fuzzy logic provides a mathematical framework to capture uncertainties related to human cognitive processes, such as thinking and reasoning. Conventional methods for knowledge representation lack the means to signify the meaning of fuzzy concepts. The authors discuss fundamental ideas and elucidate various techniques using…mehr

Produktbeschreibung
This textbook offers a unified engineering perspective on Neural Networks and Fuzzy Logic. The authors guide readers swiftly and succinctly through the intricate subjects of neural networks, fuzzy logic, and the mathematical modeling of Fuzzy Logic Control. The theory of fuzzy logic provides a mathematical framework to capture uncertainties related to human cognitive processes, such as thinking and reasoning. Conventional methods for knowledge representation lack the means to signify the meaning of fuzzy concepts. The authors discuss fundamental ideas and elucidate various techniques using numerous examples. This book is an ideal text for students majoring in Electrical and Electronics Engineering, Electronics and Communication Engineering, Computer Science Engineering, and Information Technology at the undergraduate level.
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Autorenporträt
Dr. N. Shanmugasundaram is working as a Head of the Department in Electrical and Electronics Engineering at VISTAS Chennai. Dr. K. Sushita is an Assistant Professor and Dr. T. R. Premila is an Associate Professor at the Department of Electrical and Electronics Engineering at VISTAS Chennai.