SSA of biomedical signals: A linear invariant systems approach

Detalhes bibliográficos
Autor(a) principal: Tomé, A.M.
Data de Publicação: 2010
Outros Autores: Teixeira, Ana Rita, Figueiredo, Nuno, Santos, I.M., Georgieva, P., Lang, E.W.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10773/5306
Resumo: Singular 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 lectroencephalograms (EEG).
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spelling SSA of biomedical signals: A linear invariant systems approachSSALinear invariant systemsSignal enhancementSubspace distancesSingular 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 lectroencephalograms (EEG).International Press20102010-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/5306eng1938-7989Tomé, A.M.Teixeira, Ana RitaFigueiredo, NunoSantos, I.M.Georgieva, P.Lang, E.W.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T11:08:29Zoai:ria.ua.pt:10773/5306Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:43:34.961916Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv SSA of biomedical signals: A linear invariant systems approach
title SSA of biomedical signals: A linear invariant systems approach
spellingShingle SSA of biomedical signals: A linear invariant systems approach
Tomé, A.M.
SSA
Linear invariant systems
Signal enhancement
Subspace distances
title_short SSA of biomedical signals: A linear invariant systems approach
title_full SSA of biomedical signals: A linear invariant systems approach
title_fullStr SSA of biomedical signals: A linear invariant systems approach
title_full_unstemmed SSA of biomedical signals: A linear invariant systems approach
title_sort SSA of biomedical signals: A linear invariant systems approach
author Tomé, A.M.
author_facet Tomé, A.M.
Teixeira, Ana Rita
Figueiredo, Nuno
Santos, I.M.
Georgieva, P.
Lang, E.W.
author_role author
author2 Teixeira, Ana Rita
Figueiredo, Nuno
Santos, I.M.
Georgieva, P.
Lang, E.W.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Tomé, A.M.
Teixeira, Ana Rita
Figueiredo, Nuno
Santos, I.M.
Georgieva, P.
Lang, E.W.
dc.subject.por.fl_str_mv SSA
Linear invariant systems
Signal enhancement
Subspace distances
topic SSA
Linear invariant systems
Signal enhancement
Subspace distances
description Singular 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 lectroencephalograms (EEG).
publishDate 2010
dc.date.none.fl_str_mv 2010
2010-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10773/5306
url http://hdl.handle.net/10773/5306
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1938-7989
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv International Press
publisher.none.fl_str_mv International Press
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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