Delay-dependent robust stability for Hopfield neural networks of neutral-type

Abstract

In this paper, the problem of delay-dependent robust stability for Hopfield neural networks of neutral-type is investigated. The neural networks system considered is different from the others, which has time-varying delays in neutral and discrete terms. A new class of Lyapunov–Krasovskii functional combines with the descriptor model transformation to ensure a large upper bound for time delay. The delay-dependent robust stability criterion is formulated in terms of linear matrix inequalities, in which the restriction of the derivative of time-varying delay in discrete terms is removed. Since both the neutral-delays and discrete-delays are taken into account, so the obtained criterion is more general than some existing ones. Numerical examples are given to illustrate the effectiveness of the proposed methods.