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https://hdl.handle.net/11499/7437
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ükte, Adem | - |
dc.contributor.author | Kızılkaya, Aydın | - |
dc.contributor.author | Elbi, Mehmet Doğan | - |
dc.date.accessioned | 2019-08-16T12:29:35Z | |
dc.date.available | 2019-08-16T12:29:35Z | |
dc.date.issued | 2014 | - |
dc.identifier.isbn | 18037232 (ISSN) | - |
dc.identifier.isbn | 9788026102779 | - |
dc.identifier.isbn | 9788026102762 | - |
dc.identifier.uri | https://hdl.handle.net/11499/7437 | - |
dc.identifier.uri | https://doi.org/10.1109/AE.2014.7011725 | - |
dc.description.abstract | High-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.iso | en | en_US |
dc.publisher | IEEE Computer Society | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | empirical mode decomposition | en_US |
dc.subject | high-resolution signal reconstruction | en_US |
dc.subject | multirate statistical signal processing | en_US |
dc.subject | signal denoising | en_US |
dc.subject | Gaussian noise (electronic) | en_US |
dc.subject | Iterative methods | en_US |
dc.subject | Signal analysis | en_US |
dc.subject | Signal processing | en_US |
dc.subject | Signal reconstruction | en_US |
dc.subject | White noise | en_US |
dc.subject | Additive White Gaussian noise | en_US |
dc.subject | Alternative solutions | en_US |
dc.subject | Denoising approach | en_US |
dc.subject | Empirical Mode Decomposition | en_US |
dc.subject | High resolution | en_US |
dc.subject | Low resolution | en_US |
dc.subject | Statistical signal processing | en_US |
dc.subject | Wiener filter theory | en_US |
dc.subject | Signal denoising | en_US |
dc.title | Statistical multirate high-resolution signal reconstruction using the empirical mode decomposition based denoising approach | en_US |
dc.type | Conference Object | en_US |
dc.identifier.volume | 2015-January | en_US |
dc.identifier.issue | January | en_US |
dc.identifier.startpage | 303 | |
dc.identifier.startpage | 303 | en_US |
dc.identifier.endpage | 306 | en_US |
dc.authorid | 0000-0001-7126-0289 | - |
dc.authorid | 0000-0001-8361-9738 | - |
dc.authorid | 0000-0003-2521-5115 | - |
dc.identifier.doi | 10.1109/AE.2014.7011725 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopus | 2-s2.0-84931433552 | en_US |
dc.identifier.wos | WOS:000375940400069 | en_US |
dc.owner | Pamukkale University | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.openairetype | Conference Object | - |
item.grantfulltext | none | - |
crisitem.author.dept | 10.04. Electrical-Electronics Engineering | - |
crisitem.author.dept | 10.04. Electrical-Electronics Engineering | - |
crisitem.author.dept | 10.04. 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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