• DocumentCode
    2488707
  • Title

    Complex ICA-R

  • Author

    Rajapakse, Jagath C. ; Chen, Wenda

  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    The Complex Independent Component Analysis (CICA) which extends Independent Component Analysis (ICA) to complex signals has found applications in various fields. The ICA with Reference (ICA-R) has recently gained popularity in semi-blind separation of signals when a priori information of the desired sources are available in the form of reference signals. This paper extends the framework of ICA-R to complex signals and demonstrates the use of Complex ICA-R (CICA-R) with applications to both synthetic data and real speech data. Our experiments indicate that CICA-R is more effective than ICA, ICA-R, or CICA, in separation of complex signals when reference signals relating to source signals are available.
  • Keywords
    blind source separation; independent component analysis; ICA; complex independent component analysis; reference signal; semiblind signal separation; Data mining; Electroencephalography; Frequency domain analysis; Independent component analysis; Signal to noise ratio; Speech; Time domain analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2010 International Joint Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-6916-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2010.5596453
  • Filename
    5596453