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

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 delay-interval-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.

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