Synchronization of Chaotic Cellular Neural Networks based on RÃ¶ssler Cells

Author

Rijlaarsdam, David J. ; Mladenov, Valeri M.

Author_Institution

Dept. of Mech. Eng., Eindhoven Univ. of Technol.

fYear

2006

fDate

25-27 Sept. 2006

Firstpage

41

Lastpage

43

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; RÃ¶ssler dynamics; cellular neural networks; chaos; synchronization;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/NEUREL.2006.341171

Filename

4147159