• DocumentCode
    2948857
  • Title

    A new kind of on-line prediction BSE method based on genetic algorithm

  • Author

    Lin, Bai ; Hao, Chen

  • Author_Institution
    Xian Div., China Acad. of Space Technol., Xian, China
  • fYear
    2009
  • fDate
    13-15 Nov. 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The blind signal extraction (BSE) approach based on an on-line predictor is put forward and developed recently. All the on-line predictor extraction algorithms are optimizing process based on gradient algorithm at present. The choice of initial values and learning rates could influence the performance of the algorithm. A kind of BSE approach based on genetic algorithm is put forward in the paper. The influence of initial values and learning rates on the performance of the algorithm is avoided in the kind of BSE approach based on genetic algorithm. Otherwise, various source signals are extracted by changing the order of the predictor without performing the deflation process in the algorithm. The precision is improved because the error of the extraction signals forward is not cumulated for the extraction signals backward. Simulation results illustrate the efficiency and better performance of the algorithm by separately simulating the on-line predictor extraction algorithms based on gradient algorithm and the algorithm put forward in the paper.
  • Keywords
    blind source separation; feature extraction; genetic algorithms; blind signal extraction; genetic algorithms; gradient algorithm; online prediction; Biomedical imaging; Genetic algorithms; Prediction algorithms; Predictive models; Signal processing; Signal processing algorithms; Space technology; Speech processing; Wireless communication; Working environment noise; BSE; On-line prediction; genetic algorithm; gradient;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications & Signal Processing, 2009. WCSP 2009. International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4856-2
  • Electronic_ISBN
    978-1-4244-5668-0
  • Type

    conf

  • DOI
    10.1109/WCSP.2009.5371449
  • Filename
    5371449