• DocumentCode
    1610298
  • Title

    Studies on Estimation of the Sources Number in Blind Source Separation Problems

  • Author

    Ishibashi, Takaaki ; Inoue, Katsuhiro ; Gotanda, Hiromu ; Kumamaru, Kousuke

  • Author_Institution
    Graduate Sch. of Comput. Sci. & Syst. Eng., Kyushu Inst. of Technol., Fukuoka
  • fYear
    2006
  • Firstpage
    5169
  • Lastpage
    5174
  • Abstract
    ICA (Independent Component Analysis) can separate unknown source signals from their mixture signals without information on the transfer functions, provided that the sources are statistically independent. When the number of the source signals is equal to that of the observed signals, the original sources can be recovered except for indeterminacy of scale and permutation. However, the number of the sources is unknown in a real environment. In this paper, we propose an estimation method for the number of the sources based on the joint distribution of the observed signals under two-sensor configuration. From several simulation results, it is found that the number of the sources is coincident to that of peaks in the histogram of the distribution
  • Keywords
    blind source separation; estimation theory; independent component analysis; blind source separation problems; independent component analysis; signal sources number estimation; two-sensor configuration; Acoustic noise; Blind source separation; Computer science; Frequency; Histograms; Independent component analysis; Speech recognition; Systems engineering and theory; Transfer functions; Working environment noise; Blind Source Separation; Independent Component Analysis; Sources Number Estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE-ICASE, 2006. International Joint Conference
  • Conference_Location
    Busan
  • Print_ISBN
    89-950038-4-7
  • Electronic_ISBN
    89-950038-5-5
  • Type

    conf

  • DOI
    10.1109/SICE.2006.315677
  • Filename
    4108697