Finite-time stability for memristor based switched neural networks with time-varying delays via average dwell time approach

In this paper we investigated the problem of the finite-time stability for a class of memristor based switched neural networks with time-varying delays. By constructing proper Lyapunov functionals. Based on the average dwell time technique, mode-dependent average dwell time technique and using a free-matrix-based integral inequality, Jensen's inequality are used to estimate the upper bound of the derivative of the LKF, several sufficient conditions are given to ensure the finite-time stability of the memristor-based switched neural networks with discrete and distributed delays in the sense of feasible solutions. The finite-time stability conditions here are presented in terms of linear matrix inequalities, which can be easily solved by using Matlab Tools. Finally, the numerical examples are provided to verify the effectiveness and benefit of the proposed criterion. (c) 2017 Elsevier B.V. All rights reserved.