Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/7437
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dc.contributor.authorÜkte, Adem-
dc.contributor.authorKızılkaya, Aydın-
dc.contributor.authorElbi, Mehmet Doğan-
dc.date.accessioned2019-08-16T12:29:35Z
dc.date.available2019-08-16T12:29:35Z
dc.date.issued2014-
dc.identifier.isbn18037232 (ISSN)-
dc.identifier.isbn9788026102779-
dc.identifier.isbn9788026102762-
dc.identifier.urihttps://hdl.handle.net/11499/7437-
dc.identifier.urihttps://doi.org/10.1109/AE.2014.7011725-
dc.description.abstractHigh-resolution signal reconstruction from a set of its noisy low-resolution measurements is considered. As an alternative solution to this problem, a method employing the empirical mode decomposition (EMD) based denoising approach is proposed. In the framework of the proposed method, iterative EMD interval-thresholding based denoising procedure is applied to each noisy low-resolution measurement so as to filter the additive white Gaussian noise effect on it. We then synthesize the noise-reduced low-resolution signals to form the high-resolution signal. Unlike the method using the Wiener filter theory for high-resolution signal reconstruction, the proposed method does not require knowledge of any correlation information about the desired high-resolution signal and its low-resolution versions. The validity of the proposed method is demonstrated by an audio signal reconstruction application. © 2014 University of West Bohemia.en_US
dc.language.isoenen_US
dc.publisherIEEE Computer Societyen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectempirical mode decompositionen_US
dc.subjecthigh-resolution signal reconstructionen_US
dc.subjectmultirate statistical signal processingen_US
dc.subjectsignal denoisingen_US
dc.subjectGaussian noise (electronic)en_US
dc.subjectIterative methodsen_US
dc.subjectSignal analysisen_US
dc.subjectSignal processingen_US
dc.subjectSignal reconstructionen_US
dc.subjectWhite noiseen_US
dc.subjectAdditive White Gaussian noiseen_US
dc.subjectAlternative solutionsen_US
dc.subjectDenoising approachen_US
dc.subjectEmpirical Mode Decompositionen_US
dc.subjectHigh resolutionen_US
dc.subjectLow resolutionen_US
dc.subjectStatistical signal processingen_US
dc.subjectWiener filter theoryen_US
dc.subjectSignal denoisingen_US
dc.titleStatistical multirate high-resolution signal reconstruction using the empirical mode decomposition based denoising approachen_US
dc.typeConference Objecten_US
dc.identifier.volume2015-Januaryen_US
dc.identifier.issueJanuaryen_US
dc.identifier.startpage303
dc.identifier.startpage303en_US
dc.identifier.endpage306en_US
dc.authorid0000-0001-7126-0289-
dc.authorid0000-0001-8361-9738-
dc.authorid0000-0003-2521-5115-
dc.identifier.doi10.1109/AE.2014.7011725-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-84931433552en_US
dc.identifier.wosWOS:000375940400069en_US
dc.ownerPamukkale University-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypeConference Object-
item.grantfulltextnone-
crisitem.author.dept10.04. Electrical-Electronics Engineering-
crisitem.author.dept10.04. Electrical-Electronics Engineering-
crisitem.author.dept10.04. Electrical-Electronics Engineering-
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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