Synchronization of Chaotic Cellular Neural Networks based on Rössler Cells

Synchronization of Chaotic Cellular Neural Networks based on Rössler Cells

Using and extending the approach in previous studies we demonstrate synchronization of two hyper chaotic cellular neural networks consisting of 25 cells governed by chaotic Rossler dynamics. We guarantee global asymptotic stability of the synchronization manifold by designing a nonlinear observer in...

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Bibliographische Detailangaben
Hauptverfasser: Rijlaarsdam, D.J., Mladenov, V.M.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Asymptotic stability
Boundary conditions
Cellular neural networks
Chaos
Intelligent networks
Neural networks
Nonlinear dynamical systems
Numerical simulation
Rössler dynamics
Seminars
State feedback
synchronization
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Beschreibung
Zusammenfassung:Using and extending the approach in previous studies we demonstrate synchronization of two hyper chaotic cellular neural networks consisting of 25 cells governed by chaotic Rossler dynamics. We guarantee global asymptotic stability of the synchronization manifold by designing a nonlinear observer in such a way that the resulting error system is linear and time invariant. This linear error system is evaluated and a state feedback is designed to accomplish full state synchronization. Analytical as well as numerical simulation results are presented
DOI:10.1109/NEUREL.2006.341171