Comparison of wavelets for classification of cognitive EEG signals Kognitif EEG Işaretlerinin Siniflandirilmasinda Dalgacik Türlerinin Karşilaştirilmasi

Eraldemir S. G., Yildirim E.

2015 23rd Signal Processing and Communications Applications Conference, SIU 2015, Malatya, Türkiye, 16 - 19 Mayıs 2015, ss.1381-1384, (Tam Metin Bildiri) identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu.2015.7130099
  • Basıldığı Şehir: Malatya
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.1381-1384
  • Anahtar Kelimeler: Biorthogonal, Coiflet, Discrete Wavelet Transform, EEG Classification, Symlet
  • Hatay Mustafa Kemal Üniversitesi Adresli: Evet

Özet

In this work, different wavelet types, that have been frequently used in EEG signal analysis and classification, are compared for cognitive EEG classification. EEG signals are collected from 18 healthy subjects during math processing and simple text reading. Symlet, coiflet and bior wavelet types are used for feature extraction and classification performances of BayesNet and J48 classifiers are compared. The best true positive rate of 90.6% is obtained using Boir 2.4 wavelet type with J48 classifier.