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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universidad Pedagógica y Tecnológica de Colombia
2016-09-01
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| Series: | Revista Facultad de Ingeniería |
| Subjects: | |
| Online Access: | http://revistas.uptc.edu.co/index.php/ingenieria/article/view/5300 |