Robust filtering of uncertain stochastic genetic regulatory networks with time-varying delays

被引：29
|
作者：
Wang, Wenqin [1 ]
Zhong, Shouming [1 ,2 ]
Liu, Feng [2 ,3 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Sichuan, Peoples R China
[2] Univ Elect Sci & Technol China, Minist Educ, Key Lab NeuroInformat, Chengdu 611731, Sichuan, Peoples R China
[3] Univ Elect Sci & Technol China, Sch Life Sci & Technol, Chengdu 611731, Sichuan, Peoples R China
来源：
CHAOS SOLITONS & FRACTALS | 2012年 / 45卷 / 07期
关键词：
EXPONENTIAL STABILITY; EXPRESSION; STATE; STABILIZATION; INFERENCE; SYSTEMS;
D O I：
10.1016/j.chaos.2012.03.006
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
This study is concerned with the problem of robust filtering for stochastic genetic regulatory networks with time-varying delays and parameter uncertainties. By choosing an appropriate novel Lyapunov-Krasovskii functional and establishing a new integral inequality in the stochastic setting, less conservative conditions are obtained to ensure the error systems are mean-square robustly asymptotically stable. Then the filters are designed in terms of linear matrix inequalities (LMIs) which can be checked efficiently via the LMI tool-box. What is more, the criteria can be applicable to both fast and slow time-varying delays due to our careful consideration of the ranges for the time-varying delays. Finally, two examples are presented to illustrate the effectiveness and advantages of the theoretical results. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码：915 / 929
页数：15
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