Dynamic analysis of stochastic Cohen-Grossberg neural networks with time delays

Abstract In this paper, we discuss stochastic Cohen–Grossberg neural networks with time delays. By constructing suitable Lyapunov functional and employing the semimartingale convergence theorem we give some sufficient criteria ensuring almost sure exponential stability of the networks. The results obtained are helpful to design stability of networks when stochastic noise is taken into consideration.

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