Synchronization of stochastic Markovian jump neural networks with reaction-diffusion terms

In this paper, we address the synchronization problem of a class of stochastic Markovian jump reaction-diffusion neural networks with Dirichlet boundary conditions. By using the Lyapunov–Krasovskii functional method, feedback control approach, and stochastic analysis technique, the sufficient synchronization conditions including the information of reaction-diffusion terms are obtained, which are expressed as linear matrix inequalities (LMIs). Finally, the effectiveness of the developed methods is shown by simulation examples.