Synchronization control of stochastically coupled neural networks with mixed time-delays

This paper is concerned with the synchronization control problem of an array of linearly stochastically coupled identical neural networks with discrete and distributed time-delays. Both the discrete and distributed time-delays terms are introduced to model a more realistic dynamical behavior of systems in practice, besides the stochastic coupling term. By utilizing the Lyapunov-Krasovskii functional method and linear matrix inequality (LMI) approach, several new criterions are derived to ensure the synchronization of the system studied in this paper. Meanwhile, on the basis of the stable conditions of the error system, the estimation gains of the novel delayed feedback controller can be obtained. Simulation examples are provided to present the effectiveness of the theoretical results.