Acoustic lung signals analysis based on Mel frequency cepstral coefficients and self-organizing maps
This study analyzes acoustic lung signals with different abnormalities, using Mel Frequency Cepstral Coefficients (MFCC), Self-Organizing Maps (SOM), and K-means clustering algorithm. SOM models are known as artificial neural networks than can be trained in an unsupervised or supervised manner. Both...
| Những tác giả chính: | , |
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| Định dạng: | Online |
| Ngôn ngữ: | eng |
| Được phát hành: |
Universidad Pedagógica y Tecnológica de Colombia
2016
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| Những chủ đề: | |
| Truy cập trực tuyến: | https://revistas.uptc.edu.co/index.php/ingenieria/article/view/5300 |
