Global exponential stability for discrete-time neural networks with variable delays

In this paper, the existence and the global exponential stability of the equilibrium point for a class of discrete-time BAM neural network with variable delay are investigated via Lyapunov stability theory and some analysis techniques such as using an important inequality and using norm inequalities in matrix theory. Several delay-independent sufficient conditions for the existence and the global exponential stability of the equilibrium point are derived by constructing different Lyapunov functions for different cases. Finally, two illustrative examples are given to demonstrate the effectiveness of the obtained results.

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