Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/94879
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dc.contributorDepartment of Electronic and Information Engineeringen_US
dc.creatorYe, Qen_US
dc.creatorLing, BWKen_US
dc.creatorLun, DPKen_US
dc.creatorKuang, Wen_US
dc.date.accessioned2022-08-30T08:38:10Z-
dc.date.available2022-08-30T08:38:10Z-
dc.identifier.issn1863-1703en_US
dc.identifier.urihttp://hdl.handle.net/10397/94879-
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rights© Springer-Verlag London Ltd., part of Springer Nature 2019en_US
dc.rightsThis version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s11760-019-01546-w.en_US
dc.subjectEmpirical mode decompositionen_US
dc.subjectPolyphase representationen_US
dc.subjectParallel implementationen_US
dc.subjectBandlimited signalsen_US
dc.titleParallel implementation of empirical mode decomposition for nearly bandlimited signals via polyphase representationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage225en_US
dc.identifier.epage232en_US
dc.identifier.volume14en_US
dc.identifier.issue2en_US
dc.identifier.doi10.1007/s11760-019-01546-wen_US
dcterms.abstractNearly bandlimited signals play an important role in the biomedical signal processing community. The common method to analyze these signals is via the empirical mode decomposition approach which decomposes the non-stationary signals into the sums of the intrinsic mode functions. However, this method is computational demanding. A natural idea to reduce the computational cost is via the block processing. However, the severe boundary effect would happen due to the discontinuities between two consecutive blocks. In order to solve this problem, this paper proposes to realize the parallel implementation via polyphase representation. That is, the empirical mode decomposition is implemented on each polyphase component of the original signal. Then each sub-signals are combined after upsampling. The simulation results show that our proposed method achieves the approximate intrinsic mode functions both qualitatively and quantitatively very close to the true intrinsic mode functions. Besides, compared with the conventional block processing method which significantly suffered from the boundary effect problem, our proposed method does not have this issue.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSignal, image and video processing, Mar. 2020, v. 14, no. 2, p. 225-232en_US
dcterms.isPartOfSignal, image and video processingen_US
dcterms.issued2020-03-
dc.identifier.isiWOS:000515352300001-
dc.identifier.scopus2-s2.0-85070323745-
dc.description.validate202208 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera1422-
dc.identifier.SubFormID44924-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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