Stochastic synchronization of neural networks with multiple time-varying delays and Markovian jump. Issue 3 (March 2015) - Zhou, Xianghui; Zhou, Wuneng; Yang, Jun; Hu, Xiantao
Abstract This paper addresses the stochastic synchronization problem for a class of neural networks with multiple time-varying delays and Markovian jump. By choosing a non-negative function, M-matrix technique and stochastic analysis approach, several sufficient conditions are obtained to guarantee that the error system is stable. Moreover, the update laws of the gain matrix are derived to ensure stochastic synchronization for multiple time-varying delayed drive system and response system. In particular, the M-matrix associates with the Markovian chain generated by transmission rate matrix. And the condition of M-matrix can be verified conveniently in practice. In the end, the effectiveness and potential value of the results addressed are tested by a simulation example.