A Less Conservative Stability Criterion for Delayed Stochastic Genetic Regulatory Networks | Zendy

Tingting Yu | Zendy; Jing Wang | Zendy; Xian Zhang | Zendy

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A Less Conservative Stability Criterion for Delayed Stochastic Genetic Regulatory Networks

Author(s) -

Tingting Yu,

Jing Wang,

Xian Zhang

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/768483

Subject(s) - stability (learning theory) , mathematics , stability criterion , control theory (sociology) , matlab , linear matrix inequality , mathematical optimization , circle criterion , partition (number theory) , exponential stability , computer science , nonlinear system , statistics , discrete time and continuous time , control (management) , machine learning , artificial intelligence , operating system , physics , quantum mechanics , combinatorics

This paper concerns the problem of stability analysis for delayed stochastic genetic regulatory networks. By introducing an appropriate Lyapunov-Krasovskii functional and employing delay-range partition approach, a new stability criterion is given to ensure the mean square stability of genetic regulatory networks with time-varying delays and stochastic disturbances. The stability criterion is given in the form of linear matrix inequalities, which can be easily tested by the LMI Toolbox of MATLAB. Moreover, it is theoretically shown that the obtained stability criterion is less conservative than the one in W. Zhang et al., 2012. Finally, a numerical example is presented to illustrate our theory

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