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Exponential state estimation of Markovian jumping genetic regulatory networks with mode-dependent probabilistic time-varying delays
journal contribution
posted on 2014-01-01, 00:00 authored by R Rakkiyappan, A Chandrasekar, F A Rihan, S LakshmananIn 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. © 2014 Elsevier Inc.
History
Journal
Mathematical BiosciencesVolume
251Issue
1Pagination
30 - 53Publisher DOI
ISSN
0025-5564eISSN
1879-3134Publication classification
C1.1 Refereed article in a scholarly journalCopyright notice
2014, ElsevierUsage metrics
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No categories selectedKeywords
Science & TechnologyLife Sciences & BiomedicineBiologyMathematical & Computational BiologyLife Sciences & Biomedicine - Other TopicsBernoulli distributionGenetic regulatory networksGlobal exponential stabilityLinear matrix inequalitiesMode-dependent time-varying delaysSTOCHASTIC NEURAL-NETWORKSROBUST STABILITY ANALYSISH-INFINITYNEUTRAL-TYPEPARAMETERSCRITERIONSYSTEMSDESIGNGene Regulatory NetworksMarkov ChainsMathematical ConceptsModels, GeneticModels, StatisticalStochastic ProcessesTime Factors