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Stochastic dynamics of nonautonomous Cohen-Grossberg neural networks. (English) Zbl 1217.93175
Summary: This paper is devoted to the study of the stochastic stability of a class of Cohen-Grossberg neural networks, in which the interconnections and delays are time-varying. With the help of Lyapunov function, Burkholder-Davids-Gundy inequality, and Borel-Cantell’s theory, a set of novel sufficient conditions on $p$th moment exponential stability and almost sure exponential stability for the trivial solution of the system is derived. Compared with previous published results, our method does not resort to the Razumikhin-type theorem and the semimartingale convergence theorem. Results of the development as presented in this paper are more general than those reported in some previously published papers. An illustrative example is also given to show the effectiveness of the obtained results.
##### MSC:
 93E15 Stochastic stability 92B20 General theory of neural networks (mathematical biology) 60H10 Stochastic ordinary differential equations