A novel scheme for synchronization control of stochastic neural networks with multiple time-varying delays

This paper deals with the synchronization problem for multiple time-varying delayed neural networks with the noise of Brownian motion. When the neural networks are affected by multiple time-varying delays, it is hard to deal with the synchronization for a large number of interconnected neuron units in such networks. In order to solve this problem which associates with complicated mathematic computing, a novel method is proposed to design the controller that guarantees the error system to be stable. Moreover, by using the Lyapunov-Krasovskii functional (LKF) method, stochastic analysis technique and matrix theory, a sufficient condition based on linear matrix inequality is obtained, thus the drive system can synchronize the response system. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed synchronization schemes.