Mean square stability for stochastic neural networks with distributed and interval time-varying delays

This paper is concerned with the asymptotic stability analysis problem for stochastic neural networks with distributed and interval time-varying delays. By using the stochastic analysis approach, employing some free-weighting matrices and introducing an appropriate type of Lyapunov functional which takes into account the ranges of delays, a new delay-range-dependent stability criterion is established to guarantee the delayed neural networks to be asymptotically stable in the mean square. A numerical example has also been used to demonstrate the usefulness of the main result.