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author:

Wang, Yao (Wang, Yao.) [1] | Wang, Zidong (Wang, Zidong.) [2] | Liang, Jinling (Liang, Jinling.) [3] | Li, Yurong (Li, Yurong.) [4] (Scholars:李玉榕) | Du, Min (Du, Min.) [5]

Indexed by:

EI Scopus SCIE

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 CON and therefore shows the applicability of the obtained results. (C) 2010 Elsevier B.V. All rights reserved.

Keyword:

Genetic oscillator networks Linear matrix inequality (LMI) Markovian switching Random perturbation Stochastic synchrony System biology

Community:

  • [ 1 ] [Wang, Yao]Donghua Univ, Sch Informat Sci & Technol, Shanghai 200051, Peoples R China
  • [ 2 ] [Wang, Zidong]Donghua Univ, Sch Informat Sci & Technol, Shanghai 200051, Peoples R China
  • [ 3 ] [Wang, Zidong]Brunel Univ, Dept Informat Syst & Comp, Uxbridge UB8 3PH, Middx, England
  • [ 4 ] [Liang, Jinling]Southeast Univ, Dept Math, Nanjing 210096, Peoples R China
  • [ 5 ] [Li, Yurong]Fuzhou Univ, Dept Elect Engn, Fuzhou 350002, Peoples R China
  • [ 6 ] [Du, Min]Fuzhou Univ, Dept Elect Engn, Fuzhou 350002, Peoples R China

Reprint 's Address:

  • [Wang, Zidong]Donghua Univ, Sch Informat Sci & Technol, Shanghai 200051, Peoples R China

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Source :

NEUROCOMPUTING

ISSN: 0925-2312

Year: 2010

Issue: 13-15

Volume: 73

Page: 2532-2539

1 . 4 4 2

JCR@2010

5 . 5 0 0

JCR@2023

ESI Discipline: COMPUTER SCIENCE;

JCR Journal Grade:2

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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