Passivity and robust passivity of stochastic reaction-diffusion neural networks with time-varying delays

In this paper, passivity and robust passivity for a general class of stochastic reaction-diffusion neural networks with Dirichlet boundary conditions and discrete time-varying delays are considered. With the help of inequality techniques and stochastic analysis, sufficient conditions are developed to guarantee passivity and robust passivity of the addressed neural networks. The obtained results in this study include some existing ones as special cases. A numerical example is carried out to illustrate the feasibility of the proposed theoretical criteria.