Exponential state estimation of Markovian jumping genetic regulatory networks with mode-dependent probabilistic time-varying delays

被引:24
|
作者
Rakkiyappan, R. [1 ]
Chandrasekar, A. [1 ]
Rihan, F. A. [2 ]
Lakshmanan, S. [2 ]
机构
[1] Bharathiar Univ, Dept Math, Coimbatore 641046, Tamil Nadu, India
[2] UAE Univ, Coll Sci, Dept Math Sci, Al Ain 15551, U Arab Emirates
关键词
Bernoulli distribution; Genetic regulatory networks; Global exponential stability; Linear matrix inequalities; Mode-dependent time-varying delays; STOCHASTIC NEURAL-NETWORKS; ROBUST STABILITY ANALYSIS; H-INFINITY; NEUTRAL-TYPE; PARAMETERS; CRITERION; SYSTEMS; DESIGN;
D O I
10.1016/j.mbs.2014.02.008
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In this paper, we investigate a problem of exponential state estimation for Markovian jumping genetic regulatory networks with mode-dependent probabilistic time-varying delays. A new type of mode-dependent probabilistic leakage time-varying delay is considered. Given the probability distribution of the time-delays, stochastic variables that satisfying Bernoulli random binary distribution are formulated to produce a new system which includes the information of the probability distribution. Under these circumstances, the state estimator is designed to estimate the true concentration of the mRNA and the protein of the GRNs. Based on Lyapunov-Krasovskii functional that includes new triple integral terms and decomposed integral intervals, delay-distribution-dependent exponential stability criteria are obtained in terms of linear matrix inequalities. Finally, a numerical example is provided to show the usefulness and effectiveness of the obtained results. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码:30 / 53
页数:24
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