Global exponential stability analysis of impulsive Cohen-Grossberg neural networks with delays

In this Letter, a class of Cohen-Grossberg neural networks involving variable delays and impulsive effects is considered. Global exponential stability is investigated by Lyapunov function and the well-known inequalities, and the estimated exponential convergence rate is also obtained. The proposed condition generalizes some previous results in the literature. At last, a numerical example is worked out to illustrate the effectiveness of the result.