Passivity and robust passivity of reaction-diffusion Cohen-Grossberg neural networks with multiple time-varying delays

The problem of passivity is discussed in this paper for reaction-diffusion Cohen-Grossberg neural networks (CGNNs) with multiple time-varying delays. By constructing suitable lyapunov functionals and employing some inequality techniques, several sufficient conditions guaranteeing the passivity of CGNNs are obtained. Furthermore, several criteria for robust passivity are also derived for the case that parameter uncertainties appear in CGNNs. Finally, a numerical example is given to validate the reasonableness and effectiveness of the proposed results.