Classification of respiratory sounds by using an artificial neural network

Zümray Dokur*, Tamer Ölmez

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Dergiye katkıMektupbilirkişi

20 Atıf (Scopus)

Özet

In this paper, a classification method for respiratory sounds (RSs) in patients with asthma and in healthy subjects is presented. Wavelet transform is applied to a window containing 256 samples. Elements of the feature vectors are obtained from the wavelet coefficients. The best feature elements are selected by using dynamic programming. Grow and Learn (GAL) neural network, Kohonen network and multi-layer perceptron (MLP) are used for the classification. It is observed that RSs of patients (with asthma) and healthy subjects are successfully classified by the GAL network.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)567-580
Sayfa sayısı14
DergiInternational Journal of Pattern Recognition and Artificial Intelligence
Hacim17
Basın numarası4
DOI'lar
Yayın durumuYayınlandı - Haz 2003

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