Copyright © 2011 Haibo Bao and Jinde Cao. This is an open access article distributed under the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
By using a Lyapunov-Krasovskii functional method and the stochastic
analysis technique, we investigate the problem of synchronization for discrete-time stochastic neural networks (DSNNs) with random delays. A control law is designed, and sufficient conditions
are established that guarantee the synchronization of two identical DSNNs with random delays.
Compared with the previous works, the time delay is assumed to be existent in a random fashion.
The stochastic disturbances are described in terms of a Brownian motion and the time-varying
delay is characterized by introducing a Bernoulli stochastic variable. Two examples are given to
illustrate the effectiveness of the proposed results. The main contribution of this paper is that the
obtained results are dependent on not only the bound but also the distribution probability of the
time delay. Moreover, our results provide a larger allowance variation range of the delay, and are
less conservative than the traditional delay-independent ones.