Existence and global exponential stability of periodic solution for delayed neural networks with impulsive and stochastic effects

In this paper, we investigate a class of delayed neural networks with impulsive and stochastic effects. By establishing an LL- operator delay differential inequality with impulses and using the stochastic analysis technique, some sufficient conditions are derived to ensure the existence and global exponential stability of periodic solution for the addressed neural networks. Those conditions only including related parameters of neural networks can be easily checked by simple algebraic methods. Finally, two examples and their simulations are given to show the feasibility and effectiveness of our results.