Title :
Synchronization of Chaotic Cellular Neural Networks based on Rössler Cells
Author :
Rijlaarsdam, David J. ; Mladenov, Valeri M.
Author_Institution :
Dept. of Mech. Eng., Eindhoven Univ. of Technol.
Abstract :
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
Keywords :
asymptotic stability; cellular neural nets; chaos; linear systems; state feedback; synchronisation; Rossler cell; asymptotic stability; chaotic cellular neural network; linear system; state feedback; synchronization; time invariant system; Asymptotic stability; Boundary conditions; Cellular neural networks; Chaos; Intelligent networks; Neural networks; Nonlinear dynamical systems; Numerical simulation; Seminars; State feedback; Rössler dynamics; cellular neural networks; chaos; synchronization;
Conference_Titel :
Neural Network Applications in Electrical Engineering, 2006. NEUREL 2006. 8th Seminar on
Conference_Location :
Belgrade, Serbia & Montenegro
Print_ISBN :
1-4244-0433-9
Electronic_ISBN :
1-4244-0433-9
DOI :
10.1109/NEUREL.2006.341171
