A modified hybrid neural network for pattern recognition and its application to SSW complex in EEG
Küçük Resim Yok
Tarih
2006
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SPRINGER
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, a modified hybrid neural network with asymmetric basis functions is presented for feature extraction of spike and slow wave complexes in electroencephalography (EEG). Feature extraction process has a great importance in all pattern recognition and classification problems. A gradient descent algorithm, indeed a back propagation type, is adapted to the proposed artificial neural network. The performance of the proposed network is measured using a support vector machine classifier fed by features extracted using the proposed neural network. The results show that the proposed neural network model can effectively be used in pattern recognition tasks. In experiments, real EEG data are used.
Açıklama
Anahtar Kelimeler
gradient descent algorithm, feature extraction, asymmetric basis functions, electroencephalography
Kaynak
NEURAL COMPUTING & APPLICATIONS
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
15
Sayı
1
