Finding hidden events in astrophysical data using PCA and Mixture of Gaussians clustering (Articolo in rivista)

Type

• Articolo in rivista (Classe)
• Prodotto della ricerca (Classe)

Label

• Finding hidden events in astrophysical data using PCA and Mixture of Gaussians clustering (Articolo in rivista) (literal)

Anno

• 2002-01-01T00:00:00+01:00 (literal)

Alternative label

• Funaro M., Marinaro M., Petrosino A., Scarpetta S. (2002)
  Finding hidden events in astrophysical data using PCA and Mixture of Gaussians clustering
  in Pattern analysis and applications (Print)
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Funaro M., Marinaro M., Petrosino A., Scarpetta S. (literal)

Pagina inizio

• 15 (literal)

Pagina fine

• 22 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 5-1 (literal)

Rivista

• Pattern analysis and applications (Rivista)

Note

• ISI Web of Science (WOS) (literal)

Titolo

• Finding hidden events in astrophysical data using PCA and Mixture of Gaussians clustering (literal)

Abstract

• The Principal Component Analysis (PCA) is applied to a set of astronomic data to obtain a separation between variations of luminosity and noisy fluctuations. A clustering with the Mixture of Gaussians method, performed in the principal subspace, allows us to classify the data according to the features of interest. Our results are compared with those obtained by the AGAPE (Andromeda Galaxy and Amplified Pixels Experiment) collaboration. (literal)

Prodotto di

• Institute for high performance computing and networking (ICAR) (Istituto)

Incoming links:

Prodotto

• Institute for high performance computing and networking (ICAR) (Istituto)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• Pattern analysis and applications (Rivista)