Title
Robust stability analysis for discrete-time genetic regulatory networks with probabilistic time delays
Abstract
This paper investigates the robust stability problem of a class of discrete-time genetic regulatory networks (GRNs) with probabilistic time delays. Different from the previous works, at each instant the feedback regulation delay and the translation delay are assumed to take values in two given finite sets with deterministic probability distributions. By utilizing a class of indicator functions and discrete-time Jensen inequality, delay-probability-distribution-dependent sufficient conditions are obtained in terms of linear matrix inequalities (LMIs) such that the discrete-time GRNs are robustly asymptotically stable in the mean-square sense for all admissible uncertainties and random delays. Three numerical examples are given to demonstrate the effectiveness of our theoretical results.
Year
DOI
Venue
2014
10.1016/j.neucom.2013.07.037
Neurocomputing
Keywords
Field
DocType
feedback regulation delay,asymptotically stable,robust stability analysis,admissible uncertainty,discrete-time grns,delay-probability-distribution-dependent sufficient condition,random delay,discrete-time genetic regulatory network,discrete-time jensen inequality,translation delay,probabilistic time delay
Mathematical optimization,Jensen's inequality,Finite set,Matrix (mathematics),Probability distribution,Discrete time and continuous time,Probabilistic logic,Mathematics,Stability theory
Journal
Volume
ISSN
Citations 
124,
0925-2312
7
PageRank 
References 
Authors
0.48
13
4
Name
Order
Citations
PageRank
Xiongbo Wan1595.68
Li Xu25211.98
Huajing Fang317016.86
F Yang48622.90