Binary particle swarm optimization and f-ratio for selection of features in the recognition of asphyxiated infant cry
In the infant cry classification for detecting pathological conditions using Artificial Neural Network, a common feature extraction technique employed is Mel Frequency Cepstrum Coefficient (MFCC) analysis due to its good representation properties. However, not all MFCC features are significant for c...
| Published in: | IFMBE Proceedings |
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| Main Author: | |
| Format: | Conference paper |
| Language: | English |
| Published: |
2011
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-80455162695&doi=10.1007%2f978-3-642-23508-5_18&partnerID=40&md5=74e45a52a79f9bdd6743e94583b2e69d |