Publicação
SSA of biomedical signals: A linear invariant systems approach
| 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 Electroencephalograms (EEG). |
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| Autores principais: | Figueiredo, N. |
| Outros Autores: | Georgieva, P.; Lang, E.W.; Santos, I.M.; Teixeira, A.R.; Tomé, A.M. |
| Assunto: | SSA linear invariant systems signal enhancement subspace distances |
| Ano: | 2010 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Politécnica de Coimbra |
| Idioma: | inglês |
| Origem: | Universidade Politécnica de Coimbra |
| 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 Electroencephalograms (EEG). |
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