Fuzzy and neural approaches in engineering /
Lefteri H. Tsoukalas, Robert E. Uhrig
- New York : Wiley, ℗♭1997
- xix, 587 pages : illustrations ; 24 cm
- Adaptive and learning systems for signal processing, communications, and control .
- Adaptive and learning systems for signal processing, communications, and control .
"A Wiley-Interscience publication."
Includes bibliographical references and index
Introduction to Hybrid Artificial Intelligence Systems -- Foundations of Fuzzy Approaches -- Fuzzy Relations -- Fuzzy Numbers -- Linguistic Descriptions and Their Analytical Forms -- Fuzzy Control -- Fundamentals of Neural Networks -- Backpropagation and Related Training Algorithms -- Competitive, Associative, and Other Special Neural Networks -- Dynamic Systems and Neural Control -- Practical Aspects of Using Neural Networks -- Fuzzy Methods in Neural Networks -- Neural Methods in Fuzzy Systems -- Selected Hybrid Neurofuzzy Applications -- Dynamic Hybrid Neurofuzzy Systems -- Expert Systems in Neurofuzzy Systems -- Genetic Algorithms -- Epilogue -- T Norms and S Norms 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. App.
Fuzzy and Neural Approaches in Engineering presents a detailed examination of the fundamentals of fuzzy systems and neural networks and then joins them synergistically - combining the feature extraction and modeling capabilities of the neural network with the representation capabilities of fuzzy systems. Exploring the value of relating genetic algorithms and expert systems to fuzzy and neural technologies, this forward-thinking text highlights an entire range of dynamic possibilities within soft computing With examples of specifically designed to illuminate key concepts and overcome the obstacles of notation and overly mathematical presentations often encountered in other sources, plus tables, figures, and an up-to-date bibliography, this unique work is both an important reference and a practical guide to neural networks and fuzzy systems