• DocumentCode
    1009637
  • Title

    Identifiability, separability, and uniqueness of linear ICA models

  • Author

    Eriksson, Jan ; Koivunen, Visa

  • Author_Institution
    Signal Process. Lab., Helsinki Univ. of Technol., Finland
  • Volume
    11
  • Issue
    7
  • fYear
    2004
  • fDate
    7/1/2004 12:00:00 AM
  • Firstpage
    601
  • Lastpage
    604
  • Abstract
    In this letter, we give the conditions for identifiability, separability and uniqueness of linear real valued independent component analysis (ICA) models. A theorem is formulated and a proof is provided for each of the above concepts. These results extend the conditions for solving ICA problems, originally established by Comon , to wider class of mixing models and source distributions. Examples clarifying the above concepts are presented as well.
  • Keywords
    blind source separation; identification; independent component analysis; ICA; blind methods; identifiability; independent component analysis; separability; Biomedical signal processing; Blind equalizers; Blind source separation; Data analysis; Independent component analysis; MIMO; Sensor arrays; Signal analysis; Source separation; Wireless communication;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2004.830118
  • Filename
    1306473
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1009637