Exponential stability of impulsive Cohen–Grossberg neural networks with time-varying delays and reaction–diffusion terms

In this paper, we investigate a class of impulsive Cohen–Grossberg neural networks with time-varying delays and reaction–diffusion terms. By establishing a delay differential inequality with impulsive initial conditions and employing M-matrix theory, we find some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive Cohen–Grossberg neural networks with time-varying delays and reaction–diffusion terms. In particular, the estimate of the exponential convergence rate is also provided, which depends on the system parameters and delays. Two examples are given to illustrate the results obtained here.