Robust exponential stability of discrete-time uncertain impulsive neural networks with time-varying delay

The purpose of this paper is to investigate the robust exponential stability of discrete-time uncertain impulsive neural networks with time-varying delay. By using Lyapunov functions together with Razumikhin technique, some new robust exponential stability criteria are presented. The obtained results show that the robust stability can be retained under certain impulsive perturbations for the neural network, which has the robust stability property. The obtained results also show that impulses can robustly stabilize the neural network, which does not have the robust stability property. Some examples, together with their simulations, are also given to show the effectiveness and the advantage of the presented results. It should be noted that the impulsive robust exponential stabilization result for discrete-time neural network with time-varying delay is given for the first time. Copyright (c) 2012 John Wiley & Sons, Ltd.