New Delay-Interval-Dependent Exponential Stability for Stochastic Neural Networks with Interval Time-Varying Delay and Distributed Delay

Abstract

This paper deals with the problem of exponential stability for a class of stochastic neural networks with interval time-varying delay and distributed delay. Based on the idea of nonuniform partitioning for the delay interval, new delayinterval-dependent stability conditions are proposed in terms of linear matrix inequalities (LMIs) by constructing novel Augmented Lyapunov-Krasovskii functionals. Some numerical examples are presented to show the effectiveness and improvement of the proposed method.