Stability analysis for impulsive Cohen–Grossberg neural networks with time-varying delays and distributed delays

In this paper, a class of impulsive Cohen–Grossberg neural networks with time-varying delays and distributed delays is investigated. By establishing an integro-differential inequality with impulsive initial conditions, employing the MM-matrix theory and the nonlinear measure approach, some new sufficient conditions ensuring the existence, uniqueness, global exponential stability and global robust exponential stability of equilibrium point for impulsive Cohen–Grossberg neural networks with time-varying delays and distributed delays are obtained. In particular, a more precise estimate of exponential convergence rate is provided. By comparisons and examples, it is shown that the results obtained here can extremely extend and improve previously known results.