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Neural networks and fuzzy logic textbook
Name: Neural networks and fuzzy logic textbook
File size: 503mb
Understanding Neural Networks and Fuzzy Logic: Basic Concepts and and the most used paradigms with this carefully organized state-of-the-art textbook. In this title, fuzzy logic and neural networks have been discussed in detail through illustrative examples, methods and generic applications. Extensive and. I'm sorry, this book is nearly useless. I'm a vetern C++ programmer and I tried to create a fuzzy logic system from the concepts and code in this book and it didn't.
Title, Neural Networks & Fuzzy Logic. Author, K. Vinoth Kumar. Publisher, S. K. Kataria & Sons, ISBN, , Length, pages. Understand the fundamentals of the emerging field of fuzzy neural networks, their most used paradigms with this carefully organized state-of-the-art textbook. Fuzzy logic pro vides an inference morphology that enables approximate human reasoning Introduction to Neuro-Fuzzy Systems About this Textbook.
22 Aug Best Reference Books – Neural Network and Fuzzy Logic The book also includes real world applications of neural networks in speech and. 9 Feb Book summary: This textbook explains Neural Networks, Fuzzy Logic and Genetic Algorithms from a unified engineering perspective. Why expert systems, fuzzy systems, neural networks, and hybrid systems . The book begins with an excellent introduction to AI, fuzzy-, and systems, which are based on Zadeh's fuzzy logic theory, are effective in representing explicit but. Fuzzy Logic and Neural Networks by Chennakesava R. Alavala Some of the material in this book contains timely material and thus may heavily change. Neural Networks And Fuzzy Logic, authored by K. Vinoth Kumar and R. Saravana Kumar, is a comprehensive book for Computer Engineering students studying.