Mean square exponential stability of uncertain stochastic neural networks with time-varying delay

摘要

In this paper, the mean square exponential stability problem is considered for a class of uncertain stochastic neural networks with time-varying delay. By applying a novel Lemma and Lyapunov functional method, the less conservative exponential stability criteria are derived in terms of linear matrix inequalities (LMIs). Meanwhile, the exponential convergence rate can be estimated. Two numerical examples are presented to show the effectiveness and improvement of the proposed method.