• DocumentCode
    228148
  • Title

    Neural spike representation using Cepstrum

  • Author

    Haggag, S. ; Mohamed, Salina ; Bhatti, A. ; Haggag, H. ; Nahavandi, S.

  • Author_Institution
    Centre for Intell. Syst. Res., Deakin Univ., Geelong, VIC, Australia
  • fYear
    2014
  • fDate
    9-13 June 2014
  • Firstpage
    97
  • Lastpage
    100
  • Abstract
    Neural spikes define the human brain function. An accurate extraction of spike features leads to better understanding of brain functionality. The main challenge of feature extraction is to mitigate the effect of strong background noises. To address this problem, we introduce a new feature representation for neural spikes based on Cepstrum of multichannel recordings. Simulation results indicated that the proposed method is more robust than the existing Haar wavelet method.
  • Keywords
    Haar transforms; brain; feature extraction; inverse transforms; medical computing; wavelet transforms; Cepstrum; Haar wavelet method; feature extraction; feature representation; human brain function; multichannel recordings; neural spike representation; spike features; Accuracy; Cepstrum; Clustering algorithms; Feature extraction; Neurons; Sorting; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System of Systems Engineering (SOSE), 2014 9th International Conference on
  • Conference_Location
    Adelade, SA
  • Type

    conf

  • DOI
    10.1109/SYSOSE.2014.6892470
  • Filename
    6892470
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=228148