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hal.structure.identifierInstitut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorKOMATY, Ali
hal.structure.identifierInstitut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorBOUDRAA, Abdel-Ouahab
hal.structure.identifierDepartment of Mathematics and Statistics
dc.contributor.authorNOLAN, John
hal.structure.identifierInstitut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorDARE, Delphine
dc.date.accessioned2021-05-14T09:58:20Z
dc.date.available2021-05-14T09:58:20Z
dc.date.issued2015-07
dc.identifier.issn1070-9908
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/77950
dc.descriptionEmpiricalMode Decomposition (EMD) and its extended versions such as Multivariate EMD (MEMD) are data-driven techniques that represent nonlinear and non-stationary data as a sum of a finite zero-mean AM-FM components referred to as Intrinsic Mode Functions (IMFs). The aim of this work is to analyze the behavior of EMD and MEMD in stochastic situations involving non-Gaussian noise, more precisely, we examine the case of Symmetric Alpha-Stable noise. We report numerical experiments supportingthe claim that both EMD and MEMD act, essentially, as filter banks on each channel of the input signal in the case of Symmetric Alpha Stable noise. Reported results show that, unlike EMD, MEMD has the ability to align common frequency modes across multiple channels in same index IMFs. Further, simulations show that, contrary to EMD, for MEMD the stability property is well satisfied for the modes of lower indices and this result is exploited for the estimation of the stability index of the Symmetric Alpha Stable input signal.
dc.description.abstractEnEmpiricalMode Decomposition (EMD) and its extended versions such as Multivariate EMD (MEMD) are data-driven techniques that represent nonlinear and non-stationary data as a sum of a finite zero-mean AM-FM components referred to as Intrinsic Mode Functions (IMFs). The aim of this work is to analyze the behavior of EMD and MEMD in stochastic situations involving non-Gaussian noise, more precisely, we examine the case of Symmetric Alpha-Stable noise. We report numerical experiments supportingthe claim that both EMD and MEMD act, essentially, as filter banks on each channel of the input signal in the case of Symmetric Alpha Stable noise. Reported results show that, unlike EMD, MEMD has the ability to align common frequency modes across multiple channels in same index IMFs. Further, simulations show that, contrary to EMD, for MEMD the stability property is well satisfied for the modes of lower indices and this result is exploited for the estimation of the stability index of the Symmetric Alpha Stable input signal.
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.subject.enEMD
dc.subject.enEstimation
dc.subject.enfilter banks
dc.subject.enFrequency measurement
dc.subject.enGaussian distribution
dc.subject.enMEMD
dc.subject.enNoise
dc.subject.enStability criteria
dc.subject.ensymmetric $alpha$–stable noise
dc.title.enOn the behavior of EMD and MEMD in presence of symmetric alpha-stable noise
dc.typeArticle de revue
dc.identifier.doi10.1109/LSP.2014.2371132
dc.subject.halInformatique [cs]/Traitement du signal et de l'image
bordeaux.journalIEEE Signal Processing Letters
bordeaux.page818-822
bordeaux.volume22
bordeaux.hal.laboratoriesInstitut de Mécanique et d’Ingénierie de Bordeaux (I2M) - UMR 5295*
bordeaux.issue7
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.institutionINRAE
bordeaux.institutionArts et Métiers
bordeaux.peerReviewedoui
hal.identifierhal-01089465
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01089465v1
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