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Wavelet packet decomposition of a new filter -based on underlying neural activity- for ERP classification

Raiesdana, S ; Sharif University of Technology | 2007

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  1. Type of Document: Article
  2. DOI: 10.1109/IEMBS.2007.4352681
  3. Publisher: 2007
  4. Abstract:
  5. 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. © 2007 IEEE
  6. Keywords:
  7. Enterprise resource planning ; Error analysis ; Packet networks ; Support vector machines ; Wavelet analysis ; Cross validation error ; Packet transforms ; Wavelet packet decomposition ; Neurology ; Algorithm ; Artificial neural network ; Computer program ; Evoked response ; Human ; Impedance ; Reproducibility ; Statistical analysis ; Theoretical model ; Algorithms ; Computer simulation ; Data interpretation, statistical ; Electric impedance ; Equipment design ; Evoked potentials ; Humans ; Models, theoretical ; Neural networks (computer) ; Regression analysis ; Reproducibility of results ; Signal processing ; Software ; Computer-assisted
  8. Source: 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07, Lyon, 23 August 2007 through 26 August 2007 ; 2007 , Pages 1876-1879 ; 05891019 (ISSN) ; 1424407885 (ISBN); 9781424407880 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4352681