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 :
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