Robust exponential stability analysis for stochastic genetic networks with uncertain parameters

被引:61
|
作者
Wang, Guanjun [1 ]
Cao, Jinde [1 ]
机构
[1] Southeast Univ, Dept Math, Nanjing 210096, Peoples R China
基金
中国国家自然科学基金;
关键词
Stochastic genetic network; Robust exponential stability in the mean square; Uncertain parameter; Lyapunov functional; Ito's formula; RECURRENT NEURAL-NETWORKS; REGULATORY NETWORKS; NOISE; EXPRESSION;
D O I
10.1016/j.cnsns.2009.01.004
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, the robust exponential stability problem is considered fora class of stochastic genetic networks with uncertain parameters. Under assumptions that the parameter uncertainties are norm bounded, both cases that the genetic network has or has not time delays are discussed. Sufficient conditions are derived to guarantee the robust exponential stability in the mean square of stochastic genetic networks for all admissible parameter uncertainties. By applying Lyapunov function (functional) and conducting some stochastic analysis, the stability criteria are given in the form of linear matrix inequalities (LMI's), which can be easily checked in practice. Two illustrative examples are also given to show the usefulness of the proposed criteria. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:3369 / 3378
页数:10
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