Stability and passivity analysis for uncertain discrete-time neural networks with time-varying delay

In this paper, the problem of stability and passivity analysis for uncertain discrete-time neural networks with time-varying delay is investigated. By constructing a new Lyapunov-Krasovskii functional and employing a novel summation inequality which is a discrete-time counterpart of the Wirtinger-based integral inequality, a less conservative robust stability criterion is derived in terms of linear matrix inequalities. Furthermore, a new sufficient condition is established to assure the considered neural networks to be passive. Several numerical examples are provided to demonstrate the effectiveness of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.