Fuzzy Logic Neural Networks (526 results)

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Condition: Fair. This text teaches the core concepts of fuzzy logic and neural network technologies, including back propagation and adaptive resonance theory. It includes practical applications demonstrating pattern recognition, optimization and financial modelling. The disk includes all the source code discussed.…

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Condition: New. pp. 375.

Condition: New. pp. 284 Illus.

Condition: New. pp. 375 Index 1st Edition.

Condition: New. pp. 284.

Condition: New. pp. 375.

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Condition: New. pp. 284.

pbk. Fourth Reprint. Contents 1 Introduction 2 Fuzzy Sets and Classical Sets 3 Fuzzy Relations and Classical Relations 4 Membership Functions 5 Classical Logic and Fuzzy Logic 6Fuzzy Rule Based Systems 7 Fuzzy to Crisp Conversions 8 Fuzzy Classification and Pattern Recognition 9 Fuzzy Control Systems 10 Fundamental Concepts 11 Models of Artificial Neural Systems 12 Common Neural Nets Appendix Glossary Bibliography Question BankThis book is designed to meet the requirements of Engineering students in Electronics and instrumentation electrical and electronics computer science and information technology This book explains the fundamentals of fuzzy logic and neural networks with suitable examples for better understanding Other features include Basic Fuzzy set theory is made simple Different techniques involved in Fuzzy Logic Control System Design have been highlighted Application like pattern Recognition and classification dealt in detail Different algorithms and models of artificial neural systems are given with suitable example 252 pp.…

Soft cover. Condition: New. Content: 1. Overview of Neural Networks. 2. Fundamentals of Neural Networks. 3. Feed forward Neural Networks. 4. Neural Networks Architectures. 5. Associative Memories. 6. Introduction to Fuzzy Sets: Basic Definitions and Relations. 7. Introduction to Fuzzy Logic. 8. Fuzzy Control and Stability. 8A. Advanced Process Control. 8B. Fuzzy Logic Application. This book gives a systemic account of major concepts, methodologies of artificial neural networks and to present a unified frame work that makes the subject more accessible to students and practitioners. The book emphasizes fundamental theoretical aspects of the computational capabilities and learning abilities of artificial neural networks. It integrates important theoretical results on artificial neural networks and uses them to explain a wide range of existing empirical observations and commonly used heuristics. The main audience of the book is undergraduate students in electrical engineering, computer science and engineering. It can also be used as a valuable resource for practical engineering computer scientists and others involved in research of artificial neural networks. …

Condition: Good. Good condition. With remainder mark. Disc included. (Computers, Computer Programming, Reference).