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...

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Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems 2001-09, Vol.12 (5), p.1252-1255
Main Authors: de Azevedo Botter, E., Nascimento, C.L., Yoneyama, T.
Format: Article
Language:English
Subjects:
Algorithms
Asymmetry
Basis functions
Brazil Council
Clustering algorithms
Data mining
Electrocardiography
Environmental economics
Feature extraction
Morphology
Networks
Neural networks
P waves
Pattern clustering
Testing
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Summary: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