New conditions for synchronization of a class of chaotic neural networks

Author

Zhao, Zhe ; Wu, Xueli ; Ding, Xue

Author_Institution

Coll. of Electron. Eng. & Inf., Hebei Univ. of Sci. & Technol., Shijiazhuang, China

Volume

8

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

4093

Lastpage

4096

Abstract

Chaos control and synchronization in the chaotic neural networks is discussed in this paper. Based on the stability theory of a cascade-connected system, adaptive control laws are presented to achieve chaos synchronization. The sliding model synchronization controller designed to satisfy the external disturbance vector with unknown upper bound. The advantage of the proposed controllers is that they are linear and have lower dimensions than that of the states. Simulation results for chaotic systems are provided to illustrate the effectiveness of the proposed scheme.

Keywords

adaptive control; chaotic communication; neural nets; stability; synchronisation; adaptive control; cascade connected system; chaos control; chaotic neural network; stability theory; synchronization controller; Artificial neural networks; Asymptotic stability; Chaotic communication; Delay; Lyapunov method; Synchronization; Chaotic neural networks; Sliding model control; Synchronization; Time delay;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2010 Sixth International Conference on

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-5958-2

Type

conf

DOI

10.1109/ICNC.2010.5584874

Filename

5584874