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SSA of biomedical signals: A linear invariant systems approach

dc.contributor.authorFigueiredo, N.
dc.contributor.authorGeorgieva, P.
dc.contributor.authorLang, E.W.
dc.contributor.authorSantos, I.M.
dc.contributor.authorTeixeira, A.R.
dc.contributor.authorTomé, A.M.
dc.date.accessioned2023-10-23T10:50:07Z
dc.date.available2023-10-23T10:50:07Z
dc.date.issued2010
dc.description.abstractSingular spectrum analysis (SSA) is considered from a linear invariant systems perspective. In this terminology, the extracted components are considered as outputs of a linear invariant system which corresponds to finite impulse response (FIR) filters. The number of filters is determined by the embedding dimension.We propose to explicitly define the frequency response of each filter responsible for the selection of informative components. We also introduce a subspace distance measure for clustering subspace models. We illustrate the methodology by analyzing Electroencephalograms (EEG).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.4310/SII.2010.v3.n3.a8pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.26/47395
dc.language.isoengpt_PT
dc.publisher[International Press of Boston]pt_PT
dc.subjectSSApt_PT
dc.subjectlinear invariant systemspt_PT
dc.subjectsignal enhancementpt_PT
dc.subjectsubspace distancespt_PT
dc.titleSSA of biomedical signals: A linear invariant systems approachpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlace[Boston]pt_PT
oaire.citation.endPage355pt_PT
oaire.citation.issue3pt_PT
oaire.citation.startPage345pt_PT
oaire.citation.titleStatistics and Its Interfacept_PT
oaire.citation.volume3pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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