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Fuzzy Chaotic Systems : Modeling, Control, and Applications /

By: Li, Zhong [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Fuzziness and Soft Computing: 199Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.Description: XII, 300 p. 131 illus., 4 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540332213.Subject(s): Computer science | Computers | Artificial intelligence | Dynamics | Ergodic theory | Statistical physics | Dynamical systems | Applied mathematics | Engineering mathematics | Vibration | Computer Science | Theory of Computation | Appl.Mathematics/Computational Methods of Engineering | Statistical Physics, Dynamical Systems and Complexity | Artificial Intelligence (incl. Robotics) | Dynamical Systems and Ergodic Theory | Vibration, Dynamical Systems, ControlDDC classification: 004.0151 Online resources: Click here to access online
Contents:
Fuzzy Logic and Fuzzy Control -- Chaos and Chaos Control -- Definition of Chaos in Metric Spaces of Fuzzy Sets -- Fuzzy Modeling of Chaotic Systems – I (Mamdani Model) -- Fuzzy Modeling of Chaotic Systems – II (TS Model) -- Fuzzy Control of Chaotic Systems – I (Mamdani Model) -- Adaptive Fuzzy Control of Chaotic Systems (Mamdani Model) -- Fuzzy Control of Chaotic Systems – II (TS Model) -- Synchronization of TS Fuzzy Systems -- Chaotifying TS Fuzzy Systems -- Intelligent Digital Redesign for TS Fuzzy Systems -- Spatiotemporal Chaos and Synchronization in Complex Fuzzy Systems -- Fuzzy-chaos-based Cryptography.
In: Springer eBooksSummary: "Fuzzy Chaotic Systems" provides original heuristic research achievements and insightful ideas on the interactions or intrinsic relationships between fuzzy logic and chaos theory. It presents the fundamental concepts of fuzzy logic and fuzzy control, chaos theory and chaos control, as well as thedefinition of chaos on the metric space of fuzzy sets. This monograph discusses and illustrates fuzzy modeling and fuzzy control of chaotic systems, synchronization, anti-control of chaos, intelligent digital redesign, spatiotemporal chaos and synchronization in complex fuzzy systems; as well as a practical application example of fuzzy-chaos-based cryptography. Like other very good books, this book may raise more questions than it can provide answers. It therefore generates a great potential to attract more attention to combine fuzzy systems with chaos theory and contains important seeds for future scientific research and engineering applications.
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Item type Current location Call number Status Date due Barcode Item holds
E books E books PK Kelkar Library, IIT Kanpur
Available EBK9061
Total holds: 0

Fuzzy Logic and Fuzzy Control -- Chaos and Chaos Control -- Definition of Chaos in Metric Spaces of Fuzzy Sets -- Fuzzy Modeling of Chaotic Systems – I (Mamdani Model) -- Fuzzy Modeling of Chaotic Systems – II (TS Model) -- Fuzzy Control of Chaotic Systems – I (Mamdani Model) -- Adaptive Fuzzy Control of Chaotic Systems (Mamdani Model) -- Fuzzy Control of Chaotic Systems – II (TS Model) -- Synchronization of TS Fuzzy Systems -- Chaotifying TS Fuzzy Systems -- Intelligent Digital Redesign for TS Fuzzy Systems -- Spatiotemporal Chaos and Synchronization in Complex Fuzzy Systems -- Fuzzy-chaos-based Cryptography.

"Fuzzy Chaotic Systems" provides original heuristic research achievements and insightful ideas on the interactions or intrinsic relationships between fuzzy logic and chaos theory. It presents the fundamental concepts of fuzzy logic and fuzzy control, chaos theory and chaos control, as well as thedefinition of chaos on the metric space of fuzzy sets. This monograph discusses and illustrates fuzzy modeling and fuzzy control of chaotic systems, synchronization, anti-control of chaos, intelligent digital redesign, spatiotemporal chaos and synchronization in complex fuzzy systems; as well as a practical application example of fuzzy-chaos-based cryptography. Like other very good books, this book may raise more questions than it can provide answers. It therefore generates a great potential to attract more attention to combine fuzzy systems with chaos theory and contains important seeds for future scientific research and engineering applications.

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