pth Moment exponential synchronization of impulsive fuzzy Cohen-Grossberg neural networks with variable coefficients and time-varying delays under noise perturbation

Author

Qin, Fajin ; Yao, Xiaojie

Author_Institution

Dept. of Math. & Comput. Sci., Liuzhou Teachers Coll., Liuzhou, China

fYear

2012

fDate

25-27 July 2012

Firstpage

3371

Lastpage

3376

Abstract

In this paper, we consider a class of impulsive fuzzy Cohen-Grossberg neural networks with variable coefficients and time-varying delays. By establishing an L-operator differential inequality and using stochastic analysis technique, we obtain some new sufficient conditions for the pth moment exponential synchronization of the fuzzy Cohen-Grossberg neural networks under noise perturbation. Moreover, the exponential synchronization convergence rate is s also obtained. The criteria extend and improve some earlier results.

Keywords

convergence; delays; fuzzy neural nets; perturbation techniques; stochastic processes; synchronisation; time-varying systems; L-operator differential inequality; exponential synchronization convergence rate; impulsive fuzzy Cohen-Grossberg neural networks; noise perturbation; pth moment exponential synchronization; stochastic analysis technique; sufficient conditions; time-varying delays; variable coefficients; Artificial neural networks; Delay; Noise; Stochastic processes; Synchronization; Vectors; Fuzzy Cohen-Grossberg Neural Networks(FCGGNs); Impulsive; L-operator Differential Inequality; Variable Coefficients; pth Moment Exponential Synchronization;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (CCC), 2012 31st Chinese

Conference_Location

Hefei

ISSN

1934-1768

Print_ISBN

978-1-4673-2581-3

Type

conf

Filename

6390505