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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/4090

Title: Global synchronization for discrete-time stochastic complex networks with randomly occurred nonlinearities and mixed time delays
Authors: Wang, Z
Wang, Y
Liu, Y
Keywords: Discrete time delays
Distributed time delays
Global synchronization
Randomly occurred nonlinearity (RON)
Stochastic complex networks
Stochastic coupling
Publication Date: 2010
Publisher: IEEE
Citation: IEEE Transactions on Neural Networks, 21(1): 11-25
Abstract: In this paper, the problem of stochastic synchronization analysis is investigated for a new array of coupled discrete-time stochastic complex networks with randomly occurred nonlinearities (RONs) and time delays. The discrete-time complex networks under consideration are subject to: (1) stochastic nonlinearities that occur according to the Bernoulli distributed white noise sequences; (2) stochastic disturbances that enter the coupling term, the delayed coupling term as well as the overall network; and (3) time delays that include both the discrete and distributed ones. Note that the newly introduced RONs and the multiple stochastic disturbances can better reflect the dynamical behaviors of coupled complex networks whose information transmission process is affected by a noisy environment (e.g., Internet-based control systems). By constructing a novel Lyapunov-like matrix functional, the idea of delay fractioning is applied to deal with the addressed synchronization analysis problem. By employing a combination of the linear matrix inequality (LMI) techniques, the free-weighting matrix method and stochastic analysis theories, several delay-dependent sufficient conditions are obtained which ensure the asymptotic synchronization in the mean square sense for the discrete-time stochastic complex networks with time delays. The criteria derived are characterized in terms of LMIs whose solution can be solved by utilizing the standard numerical software. A simulation example is presented to show the effectiveness and applicability of the proposed results.
Description: Copyright [2010] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
URI: http://bura.brunel.ac.uk/handle/2438/4090
DOI: http://dx.doi.org/10.1109/TNN.2009.2033599
ISSN: 1045-9227
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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