Robust passivity analysis for uncertain neural networks with leakage delay and additive time-varying delays by using general activation function

摘要

This article deals with the robust passivity analysis problem for uncertain neural networks with both leakage delay and additive time-varying delays by using a more general activation function technique. The information of activation function which is ignored in the existing results is taken into account in this paper. Based on Lyapunov stability theory, a proper Lyapunov-Krasovskii functional (LKF) with some new terms is constructed. The less conservative delay-dependent stability criteria have been obtained by applying a newly developed integral inequality that includes Jensen's inequality and a Wirtinger-based integral inequality as a special case. Some sufficient conditions are achieved to guarantee the stability and passivity of the addressed system model. All the proposed results are formulated as linear matrix inequalities (LMIs). Finally, three numerical cases are simulated to show the effectiveness and benefits of our proposed method. (C) 2017 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.