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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/4704

Title: Synchronization of stochastic genetic oscillator networks with time delays and Markovian jumping parameters
Authors: Wang, Y
Wang, Z
Liang, J
Li, Y
Du, M
Keywords: Genetic oscillator networks
System biology
Stochastic synchrony
Markovian switching
Random perturbation
Linear matrix inequality (LMI)
Publication Date: 2010
Publisher: Elsevier
Citation: Neurocomputing, 73(13-15): 2532-2539, Aug 2010
Abstract: Genetic oscillator networks (GONs) are inherently coupled complex systems where the nodes indicate the biochemicals and the couplings represent the biochemical interactions. This paper is concerned with the synchronization problem of a general class of stochastic GONs with time delays and Markovian jumping parameters, where the GONs are subject to both the stochastic disturbances and the Markovian parameter switching. The regulatory functions of the addressed GONs are described by the sector-like nonlinear functions. By applying up-to-date ‘delay-fractioning’ approach for achieving delay-dependent conditions, we construct novel matrix functional to derive the synchronization criteria for the GONs that are formulated in terms of linear matrix inequalities (LMIs). Note that LMIs are easily solvable by the Matlab toolbox. A simulation example is used to demonstrate the synchronization phenomena within biological organisms of a given GON and therefore shows the applicability of the obtained results.
Description: The official published version of the article can be found at the link below.
Sponsorship: This work was supported in part by the Biotechnology and Biological Sciences Research Council (BBSRC) of the UK under Grants BB/C506264/1 and 100/EGM17735, the Royal Society of the UK, the National Natural Science Foundation of China under Grant 60804028, the Teaching and Research Fund for Excellent Young Teachers at Southeast University of China, the International Science and Technology Cooperation Project of China under Grant 2009DFA32050, and the Alexander von Humboldt Foundation of Germany.
URI: http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V10-50CV7WB-6&_user=545641&_coverDate=08%2F31%2F2010&_rdoc=1&_fmt=high&_orig=search&_origin=search&_sort=d&_docanchor=&view=c&_searchStrId=1623191011&_rerunOrigin=google&_acct=C000027918&_version=1&_urlVersion=0&_userid=545641&md5=eadffb1287bc65bc8e9d1c8368b76e41&searchtype=a
http://bura.brunel.ac.uk/handle/2438/4704
DOI: http://dx.doi.org/10.1016/j.neucom.2010.06.006
ISSN: 0925-2312
Appears in Collections:School of Information Systems, Computing and Mathematics Research Papers
Computer Science

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