Global exponential stability of discrete-time recurrent neural networks with impulses Original Research Article

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.