Wavelet Analysis And Classification Of Mitral Regurgitation And Normal Heart Sounds Based On Artificial Neural Networks
The application of wavelet transform for the heart sounds signal is described. The performance of integral wavelet transform and discrete wavelet transform for heart sounds analysis is discussed. The features from heart sounds were obtained from integral wavelet transform and used to train and...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
2003
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| Online Access: | http://eprints.utm.my/2001/1/article178.pdf http://eprints.utm.my/2001/ |
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| _version_ | 1845470592061407232 |
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| author | Mohd Zin, Zamri Salleh, Sheikh Hussain Sulaiman, M.Daud |
| author_facet | Mohd Zin, Zamri Salleh, Sheikh Hussain Sulaiman, M.Daud |
| author_sort | Mohd Zin, Zamri |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | The application of wavelet transform for the heart
sounds signal is described. The performance of integral
wavelet transform and discrete wavelet transform for
heart sounds analysis is discussed. The features from
heart sounds were obtained from integral wavelet
transform and used to train and test the artificial neural
networks (ANN). The ANN was trained by 125 training
data and tested with 52 data. The classification accuracy
is 94.2%. |
| format | Article |
| id | my.utm.eprints-2001 |
| institution | Universiti Teknologi Malaysia |
| language | en |
| publishDate | 2003 |
| record_format | eprints |
| spelling | my.utm.eprints-20012010-06-01T03:00:12Z http://eprints.utm.my/2001/ Wavelet Analysis And Classification Of Mitral Regurgitation And Normal Heart Sounds Based On Artificial Neural Networks Mohd Zin, Zamri Salleh, Sheikh Hussain Sulaiman, M.Daud TK Electrical engineering. Electronics Nuclear engineering The application of wavelet transform for the heart sounds signal is described. The performance of integral wavelet transform and discrete wavelet transform for heart sounds analysis is discussed. The features from heart sounds were obtained from integral wavelet transform and used to train and test the artificial neural networks (ANN). The ANN was trained by 125 training data and tested with 52 data. The classification accuracy is 94.2%. 2003 Article PeerReviewed application/pdf en http://eprints.utm.my/2001/1/article178.pdf Mohd Zin, Zamri and Salleh, Sheikh Hussain and Sulaiman, M.Daud (2003) Wavelet Analysis And Classification Of Mitral Regurgitation And Normal Heart Sounds Based On Artificial Neural Networks. Signal Processing and Its Applications, 2003. Proceedings. Seventh International Symposium on . pp. 619-620. |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Mohd Zin, Zamri Salleh, Sheikh Hussain Sulaiman, M.Daud Wavelet Analysis And Classification Of Mitral Regurgitation And Normal Heart Sounds Based On Artificial Neural Networks |
| title | Wavelet Analysis And Classification Of Mitral Regurgitation And Normal Heart Sounds Based On Artificial Neural Networks |
| title_full | Wavelet Analysis And Classification Of Mitral Regurgitation And Normal Heart Sounds Based On Artificial Neural Networks |
| title_fullStr | Wavelet Analysis And Classification Of Mitral Regurgitation And Normal Heart Sounds Based On Artificial Neural Networks |
| title_full_unstemmed | Wavelet Analysis And Classification Of Mitral Regurgitation And Normal Heart Sounds Based On Artificial Neural Networks |
| title_short | Wavelet Analysis And Classification Of Mitral Regurgitation And Normal Heart Sounds Based On Artificial Neural Networks |
| title_sort | wavelet analysis and classification of mitral regurgitation and normal heart sounds based on artificial neural networks |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utm.my/2001/1/article178.pdf http://eprints.utm.my/2001/ |
| url_provider | http://eprints.utm.my/ |