Global stability of a Cohen–Grossberg neural network with both time-varying and continuous distributed delays

In this paper, a generalized neural network of Cohen–Grossberg type with both discrete time-varying and distributed unbounded delays is considered. Based on MM-matrix theory, sufficient conditions are established to ensure the existence and global attractivity of an equilibrium point. The global exponential stability of the equilibrium is also addressed, but for the model with bounded discrete time-varying delays. A comparison of results shows that these results generalize and improve those in some earlier publications.