Stability Analysis of Stochastic Reaction-Diffusion Cohen-Grossberg Neural Networks with Time-Varying Delays | Zendy

Chuangxia Huang | Zendy; Xinsong Yang | Zendy; Yigang He | Zendy

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Stability Analysis of Stochastic Reaction-Diffusion Cohen-Grossberg Neural Networks with Time-Varying Delays

Author(s) -

Chuangxia Huang,

Xinsong Yang,

Yigang He

Publication year - 2009

Publication title -

discrete dynamics in nature and society

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.264

H-Index - 39

eISSN - 1607-887X

pISSN - 1026-0226

DOI - 10.1155/2009/439173

Subject(s) - moment (physics) , artificial neural network , exponential stability , stability (learning theory) , reaction–diffusion system , diffusion , mathematics , computer science , exponential function , set (abstract data type) , algorithm , artificial intelligence , machine learning , mathematical analysis , physics , thermodynamics , quantum mechanics , nonlinear system , programming language

This paper is concerned with pth moment exponential stability of stochastic reaction-diffusion Cohen-Grossberg neural networks with time-varying delays. With the help of Lyapunov method, stochastic analysis, and inequality techniques, a set of new suffcient conditions on pth moment exponential stability for the considered system is presented. The proposed results generalized and improved some earlier publications

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