Mean square exponential stability of stochastic genetic regulatory networks with time-varying delays

被引：16
|
作者：
Wang, Zhengxia [1 ,2 ]
Liao, Xiaofeng [1 ]
Guo, Songtao [1 ]
Wu, Haixia [3 ]
机构：
[1] Chongqing Univ, Coll Comp Sci, State Key Lab Power Transmiss Equipment & Syst Se, Chongqing 400044, Peoples R China
[2] Chongqing Jiaotong Univ, Sch Sci, Chongqing 400074, Peoples R China
[3] Chongqing Educ Coll, Dept Comp & Modern Educ Technol, Chongqing 400067, Peoples R China
来源：
INFORMATION SCIENCES | 2011年 / 181卷 / 04期
关键词：
Genetic regulatory networks; Stochastic analysis; Exponential stability; Time-varying delays; Linear matrix inequalities; HOPFIELD NEURAL-NETWORKS; ROBUST STABILITY; LMI APPROACH; CRITERIA; EXPRESSION; DISCRETE; SYSTEMS; LOGIC;
D O I：
10.1016/j.ins.2010.10.007
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we study the mean square exponential stability of stochastic genetic regulatory networks with time-varying delays. Two kinds of time-varying delays are considered: one is differentiable with bounded delay derivative the other is continuous without constraints on the delay derivative. In order to investigate the mean square exponential stability in stochastic genetic regulatory networks, some novel rate-dependent/independent mean square exponential stability criteria are derived by constructing Lyapunov-Krasovskii functional. The sufficient conditions are given in terms of linear matrix inequalities. Moreover, illustrative examples are used to substantiate the effectiveness and less conservativeness of our results. (C) 2010 Elsevier Inc. All rights reserved.
引用
收藏
页码：792 / 811
页数：20
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