Impulsive controller design for exponential synchronization of delayed stochastic memristor-based recurrent neural networks

In this paper, impulsive synchronization of stochastic memristor-based recurrent neural networks with time delay is studied. One can find that the memristive connection weights have a certain relationship with the stability of the system. Based on the drive-response concept, the stochastic differential inclusions theory and the Lyapunov functional method with the impulsive delay differential inequality technique was established to guarantee the impulsive synchronization of memristor-based recurrent neural networks with stochastic effects. The obtained sufficient conditions can be checked easily by Linear Matrix Inequalities (LMI) Control Toolbox in MATLAB. Finally, a numerical example is given to illustrate the effectiveness of the theoretical results.