• DocumentCode
    3666853
  • Title

    Multi-scale wavelet kernel extreme learning machine for EEG feature classification

  • Author

    Qi Liu;Xiao-guang Zhao;Zeng-guang Hou;Hong-guang Liu

  • Author_Institution
    The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, CAS, Beijing, PRC
  • fYear
    2015
  • fDate
    6/1/2015 12:00:00 AM
  • Firstpage
    1546
  • Lastpage
    1551
  • Abstract
    In this paper, the principle of the kernel extreme learning machine (ELM) is analyzed. Based on that, we introduce a kind of multi-scale wavelet kernel extreme learning machine classifier and apply it to electroencephalographic (EEG) signal feature classification. Experiments show that our classifier achieves excellent performance.
  • Keywords
    "Kernel","Electroencephalography","Feature extraction","Training","Classification algorithms","Support vector machines","Accuracy"
  • Publisher
    ieee
  • Conference_Titel
    Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), 2015 IEEE International Conference on
  • Print_ISBN
    978-1-4799-8728-3
  • Type

    conf

  • DOI
    10.1109/CYBER.2015.7288175
  • Filename
    7288175
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3666853