Lagrange Stability for Delayed-Impulses in Discrete-Time Cohen–Grossberg Neural Networks with Delays

Abstract

In this paper, the problem of exponential Lagrange stability for delayed-impulses in discrete-time Cohen–Grossberg neural networks (CGNNs) with delays is considered. By establishing a novel convergent difference inequation, combining with inductive method and Lyapunov theory, some sufficient conditions are obtained to ensure the exponential Lagrange stability for delayed-impulses in discrete-time CGNNs. Meanwhile, the exponential convergent domain for network is given. Finally, some examples with their simulations are given to verify the effectiveness of our results.