• DocumentCode
    3730593
  • Title

    A new fast nonlinear principal component analysis algorithm for blind source separation

  • Author

    Xin Wang; Shifeng Ou; Ying Gao; Xiaofeng Guo

  • Author_Institution
    School of Opto-electronic Information Science and Technology, Yantai University, China
  • fYear
    2015
  • Firstpage
    1626
  • Lastpage
    1630
  • Abstract
    The nonlinear principal component analysis (NPCA) can be applied to solve the blind source separation (BSS) problem. By combining the optimum step size with the optimum momentum factor both derived by the decrement of the cost function of NPCA algorithm, an integration fast NPCA algorithm is proposed in this paper. Simulation experiments proved that the proposed algorithm is superior to other NPCA algorithms in convergence rate and steady error.
  • Keywords
    "Algorithm design and analysis","Convergence","Principal component analysis","Steady-state","Blind source separation","Cost function","Indexes"
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on
  • Type

    conf

  • DOI
    10.1109/FSKD.2015.7382188
  • Filename
    7382188
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3730593