A neural network with asymmetric basis functions for feature extraction of ECG P waves

In this work a simple neural network with asymmetric basis functions is proposed as a feature extractor for P waves in electrocardiographic signals (ECG). The neural network is trained using the classical backward-error-propagation algorithm. The performance of the proposed network was tested using...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2001-09, Vol.12 (5), p.1252-1255
Hauptverfasser:	de Azevedo Botter, E., Nascimento, C.L., Yoneyama, T.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Asymmetry Basis functions Brazil Council Clustering algorithms Data mining Electrocardiography Environmental economics Feature extraction Morphology Networks Neural networks P waves Pattern clustering Testing
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	In this work a simple neural network with asymmetric basis functions is proposed as a feature extractor for P waves in electrocardiographic signals (ECG). The neural network is trained using the classical backward-error-propagation algorithm. The performance of the proposed network was tested using actual ECG signals and compared with other types of neural feature extractors.
ISSN:	1045-9227 2162-237X 1941-0093 2162-2388
DOI:	10.1109/72.950154