Global exponential stability of impulsive Cohen–Grossberg neural networks with delays

In this paper, a class of Cohen–Grossberg neural networks involving delays and impulsive effects is considered. The analysis exploits a homeomorphism mapping and an appropriate Lyapunov functional, to derive easily verifiable sufficient conditions for convergence to the unique globally exponentially stable equilibrium state. The proposed conditions generalize some previous results in the literature. At last, two numerical examples are worked out to illustrate the effectiveness of our results.