Stability Criteria for Stochastic Recurrent Neural Networks with Two Time-Varying Delays and Impulses

This paper is concerned with a stability problem for a class of stochastic recurrent impulsive neural networks with both discrete and distributed time-varying delays. Based on Lyapunov-Krasovskii functional and the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of impulsive neural networks. Two numerical examples are given to illustrate the effectiveness of the stability results.