Globally Exponential Stability for Stochastic Delayed Neural Networks Under Impulsive Control

In this paper, the dynamic behaviors of a class of stochastic neural networks with time-varying delays and fixed moments of impulsive effect are considered. A new sufficient condition has been presented ensuring the global exponential stability for the equilibrium point by using Lyapunov functional method, stochastic theory and inequality technique. The results established here extend those given previously in the literatures. Finally, an example with simulation is given to show the effectiveness of the obtained results.