Wavelet packet decomposition of a new filter -- based on underlying neural activity -- for ERP classification.
This paper introduces a wavelet packet algorithm based on a new wavelet like filter created by a neural mass model in place of wavelet. The hypothesis is that the performance of an ERP based BCI system can be improved by choosing an optimal wavelet derived from underlying mechanism of ERPs. The wavelet packet transform has been chosen for its generalization in comparison to wavelet. We compared the performance of proposed algorithm with existing standard wavelets as Db4, Bior4.4 and Coif3 in wavelet packet platform. The results showed a lowest cross validation error for the new filter in classification of two different kinds of ERP datasets via a SVM classifier.
Raiesdana
Somayeh
S
Islamic Azad University, Qazvin Branch, Qazvin, Iran. Raiesdana@gmail.com
Shamsollahi
Mohammad B
MB
Hashemi
Mohamad R
MR
Rezazadeh
Iman
I
D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D017097:Electric Impedance; D004867:Equipment Design; D005071:Evoked Potentials; D006801:Humans; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D012044:Regression Analysis; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D012984:Software