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...
Egile Nagusiak: | Orjuela-Cañón, Álvaro David, Posada-Quintero, Hugo Fernando |
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Formatua: | Online |
Hizkuntza: | eng |
Argitaratua: |
Universidad Pedagógica y Tecnológica de Colombia
2016
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Gaiak: | |
Sarrera elektronikoa: | https://revistas.uptc.edu.co/index.php/ingenieria/article/view/5300 |
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