Synchronization of stochastic genetic oscillator networks with time delays and Markovian jumping parameters

Neurocomputing(2010)

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摘要
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.
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关键词
stochastic synchrony,stochastic genetic oscillator network,biochemical interaction,biological organism,synchronization criterion,synchronization phenomenon,stochastic disturbance,random perturbation,markovian parameter switching,markovian switching,stochastic gons,linear matrix inequality,system biology,time delay,genetic oscillator networks,synchronization problem,matlab toolbox,linear matrix inequality (lmi),complex system,oscillations,matrix function,genetics
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