Reduced-order state estimation of delayed memristive neural networks

The issue of reduced-order state estimation of delayed memristive neural networks is investigated in this paper for the first time. A new observer contains three gain matrices and a sign function is proposed. Then, by constructing an apposite Lyapunov-Krasovskii functional(LKF) and employing integral inequalities and linear matrix inequality technique, a time-varying delay-dependent reduced-order state estimation criterion is obtained. Finally, a numerical example is utilized to give a demonstration of the effectiveness and performance of the proposed estimation.