Novel Robust Stability Criteria For Uncertain Stochastic Neural Networks With Time-Varying Delay

This paper considers the robust stability analysis problem for a class of uncertain stochastic neural networks with time-varying delay. Based on the Lyapunov functional method, and by resorting to the new technique for estimating the upper bound of the stochastic derivative of Lyapunov functionals, the novel asymptotic stability criteria are obatined in terms of Linear matrix inequalities (LMIs). Two numerical examples are presented to show the effectiveness and the less conservativeness of the proposed method.