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Article: Robust filtering for stochastic genetic regulatory networks with time-varying delay

TitleRobust filtering for stochastic genetic regulatory networks with time-varying delay
Authors
Issue Date2009
PublisherElsevier Inc. The Journal's web site is located at http://www.elsevier.com/locate/mbs
Citation
Mathematical Biosciences, 2009, v. 220 n. 2, p. 73-80 How to Cite?
AbstractThis paper addresses the robust filtering problem for a class of linear genetic regulatory networks (GRNs) with stochastic disturbances, parameter uncertainties and time delays. The parameter uncertainties are assumed to reside in a polytopic region, the stochastic disturbance is state-dependent described by a scalar Brownian motion, and the time-varying delays enter into both the translation process and the feedback regulation process. We aim to estimate the true concentrations of mRNA and protein by designing a linear filter such that, for all admissible time delays, stochastic disturbances as well as polytopic uncertainties, the augmented state estimation dynamics is exponentially mean square stable with an expected decay rate. A delay-dependent linear matrix inequality (LMI) approach is first developed to derive sufficient conditions that guarantee the exponential stability of the augmented dynamics, and then the filter gains are parameterized in terms of the solution to a set of LMIs. Note that LMIs can be easily solved by using standard software packages. A simulation example is exploited in order to illustrate the effectiveness of the proposed design procedures. © 2009 Elsevier Inc. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/124817
ISSN
2015 Impact Factor: 1.256
2015 SCImago Journal Rankings: 0.719
ISI Accession Number ID
Funding AgencyGrant Number
Biotechnology and Biological Sciences Research Council (BBSRC) of the U.KBB/C506264/1
100/EGM17735
Royal Society of the U.K.
Research Grants Council of Hong KongHKU 7031/06P
National Natural Science Foundation of China60804028
Alexander von Humboldt Foundation of Germany
Funding Information:

This work was supported in part by the Biotechnology and Biological Sciences Research Council (BBSRC) of the U.K. under Grants BB/C506264/1 and 100/EGM17735, an International joint Project sponsored by the Royal Society of the U.K., the Research Grants Council of Hong Kong under Grant HKU 7031/06P, the National Natural Science Foundation of China under Grant 60804028, and the Alexander von Humboldt Foundation of Germany.

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorWei, Gen_HK
dc.contributor.authorWang, Zen_HK
dc.contributor.authorLam, Jen_HK
dc.contributor.authorFraser, Ken_HK
dc.contributor.authorRao, GPen_HK
dc.contributor.authorLiu, Xen_HK
dc.date.accessioned2010-10-31T10:55:52Z-
dc.date.available2010-10-31T10:55:52Z-
dc.date.issued2009en_HK
dc.identifier.citationMathematical Biosciences, 2009, v. 220 n. 2, p. 73-80en_HK
dc.identifier.issn0025-5564en_HK
dc.identifier.urihttp://hdl.handle.net/10722/124817-
dc.description.abstractThis paper addresses the robust filtering problem for a class of linear genetic regulatory networks (GRNs) with stochastic disturbances, parameter uncertainties and time delays. The parameter uncertainties are assumed to reside in a polytopic region, the stochastic disturbance is state-dependent described by a scalar Brownian motion, and the time-varying delays enter into both the translation process and the feedback regulation process. We aim to estimate the true concentrations of mRNA and protein by designing a linear filter such that, for all admissible time delays, stochastic disturbances as well as polytopic uncertainties, the augmented state estimation dynamics is exponentially mean square stable with an expected decay rate. A delay-dependent linear matrix inequality (LMI) approach is first developed to derive sufficient conditions that guarantee the exponential stability of the augmented dynamics, and then the filter gains are parameterized in terms of the solution to a set of LMIs. Note that LMIs can be easily solved by using standard software packages. A simulation example is exploited in order to illustrate the effectiveness of the proposed design procedures. © 2009 Elsevier Inc. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier Inc. The Journal's web site is located at http://www.elsevier.com/locate/mbsen_HK
dc.relation.ispartofMathematical Biosciencesen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in <Mathematical Biosciences>. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in PUBLICATION, [VOL 220, ISSUE 2, (AUG 2009)] DOI eid_2-s2.0-67650682711-
dc.subject.meshAlgorithmsen_HK
dc.subject.meshComputer Simulationen_HK
dc.subject.meshFeedback, Physiological - geneticsen_HK
dc.subject.meshGene Regulatory Networks - physiologyen_HK
dc.subject.meshKineticsen_HK
dc.subject.meshLinear Modelsen_HK
dc.subject.meshModels, Geneticen_HK
dc.subject.meshProteins - metabolismen_HK
dc.subject.meshRNA, Messenger - metabolismen_HK
dc.subject.meshStochastic Processesen_HK
dc.subject.meshTime Factorsen_HK
dc.titleRobust filtering for stochastic genetic regulatory networks with time-varying delayen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0025-5564&volume=220&issue=2&spage=73&epage=80&date=2009&atitle=Robust+filtering+for+stochastic+genetic+regulatory+networks+with+time-varying+delayen_HK
dc.identifier.emailLam, J:james.lam@hku.hken_HK
dc.identifier.authorityLam, J=rp00133en_HK
dc.description.naturepostprint-
dc.identifier.doi10.1016/j.mbs.2009.04.002en_HK
dc.identifier.pmid19393668-
dc.identifier.scopuseid_2-s2.0-67650682711en_HK
dc.identifier.hkuros179591en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-67650682711&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume220en_HK
dc.identifier.issue2en_HK
dc.identifier.spage73en_HK
dc.identifier.epage80en_HK
dc.identifier.isiWOS:000269046800001-
dc.publisher.placeUnited Statesen_HK
dc.relation.projectDecay rate estimation and synthesis of functional differential systems via semi-definite programming-
dc.identifier.scopusauthoridWei, G=8365213900en_HK
dc.identifier.scopusauthoridWang, Z=35231712300en_HK
dc.identifier.scopusauthoridLam, J=7201973414en_HK
dc.identifier.scopusauthoridFraser, K=8986916900en_HK
dc.identifier.scopusauthoridRao, GP=7403993176en_HK
dc.identifier.scopusauthoridLiu, X=35290922200en_HK
dc.identifier.citeulike5334929-

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