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Greedy kernel PCA applied to single-channel EEG eecordings

dc.contributor.authorTomé, A. M.
dc.contributor.authorTeixeira, Ana
dc.contributor.authorLang, E.W.
dc.contributor.authorSilva, A. Martins
dc.date.accessioned2023-10-23T09:02:23Z
dc.date.available2023-10-23T09:02:23Z
dc.date.issued2007
dc.description.abstractIn this work, we propose the correction of univariate, single channel EEGs using a kernel technique. The EEG signal is embedded in its time-delayed coordinates obtaining a multivariate signal. A kernel subspace technique is used for denoising and artefact extraction. The proposed kernel method follows a greedy approach to use a reduced data set to compute a new basis onto which to project the mapped data in feature space. The pre-image of the reconstructed multivariate signal is computed and the embedding is reverted. The resultant signal is the high amplitude artifact which must be subtracted from the original signal to obtain a corrected version of the underlying signal.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.urihttp://hdl.handle.net/10400.26/47382
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.titleGreedy kernel PCA applied to single-channel EEG eecordingspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceLyonpt_PT
oaire.citation.endPage5444pt_PT
oaire.citation.startPage5441pt_PT
oaire.citation.titleProceedings of the 29th Annual InternationalConference of the IEEE EMBSpt_PT
person.familyNameTeixeira
person.givenNameAna
person.identifier.ciencia-idD619-A151-8BE2
person.identifier.orcid0000-0002-8120-0148
person.identifier.ridA-3100-2014
person.identifier.scopus-author-id7202385348
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationc1ff686d-c3d3-4658-96c6-a1f62a52777a
relation.isAuthorOfPublication.latestForDiscoveryc1ff686d-c3d3-4658-96c6-a1f62a52777a

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