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Classification of Lung Sounds using Higher-Order Statistics: A divide-and-conquer approach
Highlights • A pattern recognition system to classify five lung sounds is proposed. • The system is based on HOS and on a divide-and-conquer approach. • The proposed approach uses Genetic Algorithms to dimensionality reduction, and k-Nearest Neighbor and Naive Bayes to recognize the signals. • The s...
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| Published in: | Computer methods and programs in biomedicine 2016-06, Vol.129, p.12-20 |
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| Main Authors: | , , |
| Format: | Article |
| Language: | English |
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| container_end_page | 20 |
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| container_title | Computer methods and programs in biomedicine |
| container_volume | 129 |
| creator | Naves, Raphael Barbosa, Bruno H.G Ferreiradanton@deg.ufla.br, Danton D |
| description | Highlights • A pattern recognition system to classify five lung sounds is proposed. • The system is based on HOS and on a divide-and-conquer approach. • The proposed approach uses Genetic Algorithms to dimensionality reduction, and k-Nearest Neighbor and Naive Bayes to recognize the signals. • The system achieved a high classification accuracy and can be implemented in an embedded system. |
| doi_str_mv | 10.1016/j.cmpb.2016.02.013 |
| format | article |
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| ispartof | Computer methods and programs in biomedicine, 2016-06, Vol.129, p.12-20 |
| issn | 0169-2607 1872-7565 |
| language | eng |
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| source | Elsevier |
| subjects | Acoustics Algorithms Bayes Theorem Classification Classifiers Feature extraction Genetic Algorithm Genetic algorithms Higher-order statistics Humans Internal Medicine Lung sounds Lungs Models, Statistical Other Pattern recognition Respiratory Sounds - classification Statistics Training |
| title | Classification of Lung Sounds using Higher-Order Statistics: A divide-and-conquer approach |
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