
doi: 10.1155/2011/297147
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 pth moment exponential stability and almost sure exponential stability for the trivial solution of the system is derived. Compared with the 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.
Lyapunov function, Borel-Cantell's theory, exponential stability, stochastic stability, QA1-939, Cohen-Grossberg neural networks, Stochastic stability in control theory, Neural networks for/in biological studies, artificial life and related topics, Burkholder-Davids-Gundy inequality, Mathematics, Stochastic ordinary differential equations (aspects of stochastic analysis)
Lyapunov function, Borel-Cantell's theory, exponential stability, stochastic stability, QA1-939, Cohen-Grossberg neural networks, Stochastic stability in control theory, Neural networks for/in biological studies, artificial life and related topics, Burkholder-Davids-Gundy inequality, Mathematics, Stochastic ordinary differential equations (aspects of stochastic analysis)
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