Passivity analysis and state estimation for a class of memristor-based neural networks with multiple proportional delays

This paper is concerned with the problem of a passivity analysis for a class of memristor-based neural networks with multiple proportional delays and the state estimator is designed for the memristive system through the available output measurements. By constructing a proper Lyapunov-Krasovskii functional, new criteria are obtained for the passivity and state estimation of the memristive neural networks. Finally, a numerical example is given to illustrate the feasibility of the theoretical results.