Relaxed dissipativity criteria for memristive neural networks with leakage and time-varying delays

Abstract

In this paper, the problem of strict (Q,S,R)-γ-dissipativity analysis for memristive neural networks (MNNs) with leakage and time-varying delays is studied. By applying nonsmooth analysis, MNNs are converted into the conventional neural networks (NNs). Based on the construction of a novel Lyapunov–Krasovskii functional (LKF), the relaxed dissipativity criteria are obtained by combining Wirtinger-based integral inequality with free-weighting matrices technique. This superior proposed criteria do not really require all the symmetric matrices involved in the employed quadratic to be positive definite. Moreover, the derived criteria are less conservative. Finally, two numerical examples are given to show the effectiveness and less conservatism of the proposed criteria.