Filtering time series using point-wise dimension: application to the study of electrocardiograms (Articolo in rivista)

Type
Label
  • Filtering time series using point-wise dimension: application to the study of electrocardiograms (Articolo in rivista) (literal)
Anno
  • 2006-01-01T00:00:00+01:00 (literal)
Alternative label
  • Aldo Casaleggio; Angelo Corana (2006)
    Filtering time series using point-wise dimension: application to the study of electrocardiograms
    in Chaos and complexity letters
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Aldo Casaleggio; Angelo Corana (literal)
Pagina inizio
  • 23 (literal)
Pagina fine
  • 31 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.zentralblatt-math.org/zbmath/search/?q=an%3A1131.37068 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 2 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 1 (literal)
Note
  • entralblatt MATH Database (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • IBF-CNR, Genova, Italy; IEIIT-CNR, Genova, Italy (literal)
Titolo
  • Filtering time series using point-wise dimension: application to the study of electrocardiograms (literal)
Abstract
  • This paper deals with dimension estimation from time series. We propose a procedure based on the pointwise dimension for selecting subsets of the time series, and of the corresponding trajectory in the phase space, depending on the choice of reference point. For a given reference point, this filtering action is obtained by considering points within the scaling region, and results vary with the embedding dimension. The procedure is applied to the analysis of a few electrocardiograms and preliminary results show that a suitable choice of reference point allows investigation of the various underlying mechanisms involved in heart activity. Although in the early stages of development, the proposed method may be a useful tool for the study of the underlying mechanisms which can be observed in nonlinear dynamical systems. (literal)
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