Dependent component analysis for cosmology: a case study (Contributo in atti di convegno)

Type
Label
  • Dependent component analysis for cosmology: a case study (Contributo in atti di convegno) (literal)
Anno
  • 2010-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1007/978-3-642-15995-4_67 (literal)
Alternative label
  • Kuruoglu E. E. (2010)
    Dependent component analysis for cosmology: a case study
    in LVA/ICA 2010 - Latent Variable Analysis and Signal Separation. 9th International Conference, St. Malo, France, 27-30 September 2010
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Kuruoglu E. E. (literal)
Pagina inizio
  • 538 (literal)
Pagina fine
  • 545 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.springerlink.com/content/l04675g2616k2724/ (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 6365 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • In: LVA/ICA 2010 - Latent Variable Analysis and Signal Separation. 9th International Conference (St. Malo, France, 27-30 September 2010). Proceedings, pp. 538 - 545. Vincent Vigneron, Vicente Zarzoso, Eric Moreau, Rémi Gribonval, Emmanuel Vincent (eds.). (Lecture Notes in Computer Science, vol. 6365). Springer, 2010. (literal)
Note
  • PuMa (literal)
  • Scopu (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR-ISTI, Pisa, Italy (literal)
Titolo
  • Dependent component analysis for cosmology: a case study (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-3-642-15995-4 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
  • Vincent Vigneron, Vicente Zarzoso, Eric Moreau, Rémi Gribonval, Emmanuel Vincent (literal)
Abstract
  • In this paper, we discuss various dependent component analysis approaches available in the literature and study their performances on the problem of separation of dependent cosmological sources from multichannel microwave radiation maps of the sky. Realisticaly simulated cosmological radiation maps are utilised in the simulations which demonstrate the superior performance obtained by tree-dependent component analysis and correlated component analysis methods when compared to classical ICA. (literal)
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