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Sampled-Data Stabilization for Fuzzy Genetic Regulatory Networks with Leakage Delays

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dc.contributor.authorAli, M. Syed-
dc.contributor.authorGunasekaran, N.-
dc.contributor.authorAhn, Choon Ki-
dc.contributor.authorShi, Peng-
dc.date.accessioned2021-09-02T16:24:21Z-
dc.date.available2021-09-02T16:24:21Z-
dc.date.created2021-06-16-
dc.date.issued2018-01-
dc.identifier.issn1545-5963-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/78071-
dc.description.abstractThis paper deals with the sampled-data stabilization problem for Takagi-Sugeno (T-S) fuzzy genetic regulatory networks with leakage delays. A novel Lyapunov-Krasovskii functional (LKF) is established by the non-uniform division of the delay intervals with triplex and quadruplex integral terms. Using such LKFs for constant and time-varying delay cases, new stability conditions are obtained in the T-S fuzzy framework. Based on this, a new condition for the sampled-data controller design is proposed using a linear matrix inequality representation. A numerical result is provided to show the effectiveness and potential of the developed design method.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherIEEE COMPUTER SOC-
dc.subjectTIME-VARYING DELAYS-
dc.subjectGLOBAL EXPONENTIAL STABILITY-
dc.subjectROBUST H-INFINITY-
dc.subjectBAM NEURAL-NETWORKS-
dc.subjectSTOCHASTIC STABILITY-
dc.subjectDISTRIBUTED DELAYS-
dc.subjectSTATE ESTIMATOR-
dc.subjectSYSTEMS-
dc.subjectPERFORMANCE-
dc.subjectDISCRETE-
dc.titleSampled-Data Stabilization for Fuzzy Genetic Regulatory Networks with Leakage Delays-
dc.typeArticle-
dc.contributor.affiliatedAuthorAhn, Choon Ki-
dc.identifier.doi10.1109/TCBB.2016.2606477-
dc.identifier.scopusid2-s2.0-85041798718-
dc.identifier.wosid000424479500024-
dc.identifier.bibliographicCitationIEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, v.15, no.1, pp.271 - 285-
dc.relation.isPartOfIEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS-
dc.citation.titleIEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS-
dc.citation.volume15-
dc.citation.number1-
dc.citation.startPage271-
dc.citation.endPage285-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryBiochemical Research Methods-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryMathematics, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryStatistics & Probability-
dc.subject.keywordPlusTIME-VARYING DELAYS-
dc.subject.keywordPlusGLOBAL EXPONENTIAL STABILITY-
dc.subject.keywordPlusROBUST H-INFINITY-
dc.subject.keywordPlusBAM NEURAL-NETWORKS-
dc.subject.keywordPlusSTOCHASTIC STABILITY-
dc.subject.keywordPlusDISTRIBUTED DELAYS-
dc.subject.keywordPlusSTATE ESTIMATOR-
dc.subject.keywordPlusSYSTEMS-
dc.subject.keywordPlusPERFORMANCE-
dc.subject.keywordPlusDISCRETE-
dc.subject.keywordAuthorGenetic regulatory network-
dc.subject.keywordAuthorinterval time-varying delay-
dc.subject.keywordAuthorsampled-data stabilization-
dc.subject.keywordAuthorTakagi-Sugeno fuzzy model-
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