pth moment exponential stability for impulsive stochastic delayed neural networks

This paper is concerned with pth moment exponential stability of stochastic delayed neural networks. By using the Lyapunov function method, some stability criteria of impulsive stochastic delayed systems are obtained, and these results are applied to the study on the stability criteria of stochastic delayed neural networks. It is shown that if the continuous stochastic delayed neural network is stable and the impulsive effects are destabilizing, then the stochastic delayed neural network is exponentially stable with respect to a lower bound of the impulsive interval. Moreover, if the continuous stochastic delayed neural network is not stable, the impulsive effects can successfully stabilize the delayed neural network for a given upper bound of the impulsive interval. One example is presented to demonstrate the usefulness of the proposed results.