Anti-synchronization of stochastic delayed Cohen-Grossberg neural networks

Author

Yang Ye ; Zhu Quanxin ; Wang Xiaoxi ; He Tingting ; Zhang Wenjie

Author_Institution

Fac. of Sci., Ningbo Univ., Ningbo, China

fYear

2011

fDate

22-24 July 2011

Firstpage

2626

Lastpage

2631

Abstract

In this paper, we study the anti-synchronization problem for a class of stochastic delayed Cohen-Grossberg neural networks. By using a Lyapunov-Krasovskii functional, Ito´s formula and stochastic analysis theory, some sufficient conditions are given to ensure that the considered system achieves anti-synchronization. In particular, our results are expresses in term of linear matrix inequalities, which are easy to verify. Finally, a simulation example is provided to show that the suggested method is effective.

Keywords

Lyapunov matrix equations; delays; linear matrix inequalities; neural nets; stochastic processes; Ito´s formula; Lyapunov-Krasovskii functional; antisynchronization problem; linear matrix inequalities; stochastic analysis theory; stochastic delayed Cohen-Grossberg neural networks; Adaptive systems; Artificial neural networks; Chaos; Delay; Linear matrix inequalities; Synchronization; Anti-synchronization; Cohen-Grossberg neural networks; Exponential synchronization; Linear matrix inequality; Stochastic neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (CCC), 2011 30th Chinese

Conference_Location

Yantai

ISSN

1934-1768

Print_ISBN

978-1-4577-0677-6

Electronic_ISBN

1934-1768

Type

conf

Filename

6000411