Abstract
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, boundness of the activation functions.
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