Exponential Stability of Discrete-Time Cohen-Grossberg Neural Networks with Delays

摘要

Discrete-time Cohen-Grossberg neural networks(CGNNs) are studied in this paper. Several sufficient conditions are obtained to ensure .the global exponential stability of the discrete-time systems of CGNNs with delays based on Lyapunov methods. The obtained results have not assume the symmetry of the connection matrix, and monotonicity, bound-ness of the activation functions.