LMI conditions for robust stability analysis of stochastic hopfield neural networks with interval time-varying delays and linear fractional uncertainties

In this paper, the delay-dependent robust stability for a class of stochastic neural networks with linear fractional uncertainties is studied. The time-varying delay is assumed to belong to an interval, which means that the lower and upper bounds of interval time-varying delays are available. Based on the Lyapunov-Krasovskii functional, stochastic stability theory and some inequality techniques, delay-interval dependent stability criteria are obtained in terms of linear matrix inequalities (LMIs). In order to derive less conservative results, few free-weighting matrices are introduced. Three numerical examples are presented to show the effectiveness and improvement of the proposed method.