Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/96141
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Type: Journal article
Title: Synchronization of delayed neural networks with Lévy noise and Markovian switching via sampled data
Author: Yang, J.
Zhou, W.
Shi, P.
Yang, X.
Zhou, X.
Su, H.
Citation: Nonlinear Dynamics, 2015; 81(3):1179-1189
Publisher: Springer
Issue Date: 2015
ISSN: 0924-090X
1573-269X
Statement of
Responsibility: 
Jun Yang, Wuneng Zhou, Peng Shi, Xueqing Yang, Xianghui Zhou, Hongye Su
Abstract: In this paper, the problem of synchronization via sampled-data control is considered for stochastic delayed neural networks with Lévy noise and Markovian switching. The purpose of the problem addressed is to derive a sufficient condition and a sampled-data control law such that the dynamics of the error system is stable in mean square, and thus the synchronization can be achieved for the master system and the slave system. By generalized Itô’s formula and the construction of Lyapunov functional, an LMI-based sufficient condition is established to ensure the synchronization of the two systems. The control law is determined simultaneously, which depends on the switching mode, time delay, and the upper bound of sampling intervals. A numerical example is provided to verify the usefulness of the proposed criterion.
Keywords: Lévy noise; Lyapunov functional; Markovian switching; neural networks; sampled-data; synchronization
Rights: © Springer Science+Business Media Dordrecht 2015
RMID: 0030032814
DOI: 10.1007/s11071-015-2059-4
Grant ID: http://purl.org/au-research/grants/arc/DP140102180
http://purl.org/au-research/grants/arc/LP140100471
Appears in Collections:Electrical and Electronic Engineering publications

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