• DocumentCode
    1941159
  • Title

    Independent Sub-Band Functions: Model and Applications

  • Author

    Cheng, Xiefeng ; Zheng, Yan ; Tao, Yewei ; Chen, Zhengyu ; Chen, Yuehui

  • Author_Institution
    Univ. of Jinan, Jinan
  • fYear
    2007
  • fDate
    12-17 Aug. 2007
  • Firstpage
    361
  • Lastpage
    365
  • Abstract
    The paper presented a new signal processing technique to accomplish blind source separation when given only a single-channel mixture signal. One signal source can be generated by a set of weighted linear superposition of the time domain sub-band functions with independent component characteristic. By combining the independent sub-band function components into the single-channel mixture signal, making the single-channel mixture signal is transformed into a multi-dimensional vector from one-dimensional. Thus ICA can be applied to separate the extended single-channel mixture signal. The simulation results demonstrated the effectiveness and adaptability of the proposed method. What is more, similitude phase graph is also proposed in this paper, which can show the performance of blind separation algorithm straightly.
  • Keywords
    blind source separation; independent component analysis; ICA; blind separation algorithm; blind source separation; independent component characteristic; independent sub-band functions:; multi-dimensional vector; signal processing technique; single-channel mixture signal; time domain sub-band functions; weighted linear superposition; Neural networks; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2007. IJCNN 2007. International Joint Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1379-9
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2007.4370983
  • Filename
    4370983