• DocumentCode
    1627909
  • Title

    Novel Approach for Blind Source Separation

  • Author

    Shiblee, Md ; Chandra, B.

  • Author_Institution
    Coll. of Comput. Sci., King Khalid Univ., Abha, Saudi Arabia
  • fYear
    2013
  • Firstpage
    204
  • Lastpage
    208
  • Abstract
    An attempt has been made to use efficient Neuron model for blind source separation. Generalized Harmonic Mean Neuron (GHMN) has been used as the neuron model. GHMN model is based on generalized harmonic mean of the inputs applied on it. Information-maximization approach has been used for training the neuron model. In this paper, it has been demonstrated how efficiently the GHMN model can be used for blind source separation. It has been shown on a generated mixture of finger prints and a real life mixture of finger prints (for blind source separation) that the new neuron model performs far superior as compared to the conventional neuron model.
  • Keywords
    blind source separation; fingerprint identification; neural nets; optimisation; GHMN model; blind source separation; fingerprint separation; generalized harmonic mean neuron; information-maximization approach; neuron model; Blind source separation; Fingerprint recognition; Fingers; Harmonic analysis; Mathematical model; Neurons; Vectors; Blind source separation; Finger print separation; Generalized Harmonic based neuron model; Information maximization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Developments in eSystems Engineering (DeSE), 2013 Sixth International Conference on
  • Conference_Location
    Abu Dhabi
  • ISSN
    2161-1343
  • Print_ISBN
    978-1-4799-5263-2
  • Type

    conf

  • DOI
    10.1109/DeSE.2013.44
  • Filename
    7041117