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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| Veröffentlicht in: | IEEE transaction on neural networks and learning systems 2001-09, Vol.12 (5), p.1252-1255 |
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| container_title | IEEE transaction on neural networks and learning systems |
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| creator | de Azevedo Botter, E. Nascimento, C.L. Yoneyama, T. |
| description | 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. |
| doi_str_mv | 10.1109/72.950154 |
| format | Article |
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| identifier | ISSN: 1045-9227 |
| ispartof | IEEE transaction on neural networks and learning systems, 2001-09, Vol.12 (5), p.1252-1255 |
| issn | 1045-9227 2162-237X 1941-0093 2162-2388 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| 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 |
| title | A neural network with asymmetric basis functions for feature extraction of ECG P waves |
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