Stability analysis of delayed cellular neural networks with impulsive effects

This paper focuses on the problem of exponential stability analysis of delayed cellular neural networks (DCNNs) with impulsive effects. The time delay is allowed to be time varying. By utilizing the piecewise linear property of the activation function of DCNNs and applying Razumikhin-type analysis techniques, two different types of delay-independent criteria for exponential stability of DCNNs with impulsive effects are derived in terms of linear matrix inequalities. The first of the two criteria can be used to design a reduced-order impulsive control law for unstable DCNNs. The other criterion shows that local stability of the equilibriums of the original DCNNs can still be retained under certain impulsive perturbation. Two numerical examples illustrated the efficiency of the proposed method.