Global exponential stability for a class of impulsive BAM neural networks with distributed delays

In this paper, the exponential stability is investigated for a class of BAM neural networks with distributed delays and nonlinear impulsive operators. By using Lyapunov functions and applying the Razumikhin technique, delay-independent sufficient conditions ensuring the global exponential stability of equilibrium points are derived. These results can easily be utilized to design and verify globally stable networks. An illustrative example is given to demonstrate the effectiveness of the obtained results.