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This paper discusses synchronization problem of two delayed stochastic neural networks. By constructing the Lyapunov functions, using stochastic analysis technique, some sufficient conditions guaranteeing the synchronization in mean square for… Click to show full abstract
This paper discusses synchronization problem of two delayed stochastic neural networks. By constructing the Lyapunov functions, using stochastic analysis technique, some sufficient conditions guaranteeing the synchronization in mean square for the drive system with the response system have been derived in terms of linear matrix inequalities (LMIs) approach. Moreover, the main feature of this paper lies in that the present results are applicable for the drive system and the response system which all are considered not only in complex-valued domain but also with stochastic noise case. Two numerical examples are given to illustrate the effectiveness and merits of the present results.
Journal Title: IEEE Access
Year Published: 2019
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