Abstract
In this paper, the global exponential stability of a discrete-time recurrent neural network with impulses is discussed. First, conditions for existence and uniqueness of the equilibrium point of these neural networks are introduced; second, some sufficient rules for the global exponential stability of these neural networks are obtained by using the Lyapunov function.
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