Skip to Main content Skip to Navigation
Conference papers

Discrete Wavelet based Features for PCG Signal Classification using Hidden Markov Models

Rima Touahria Abdenour Hacine-Gharbi Philippe Ravier 1, 2
1 PRISME - Laboratoire pluridisciplinaire de recherche en ingénierie des systèmes, mécanique et énergétique
2 IRAuS/Signal
PRISME - Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique
Document type :
Conference papers
Complete list of metadata
https://hal-univ-orleans.archives-ouvertes.fr/hal-03520136
Contributor : Philippe Ravier Connect in order to contact the contributor
Submitted on : Monday, January 10, 2022 - 7:13:42 PM
Last modification on : Tuesday, January 11, 2022 - 3:27:06 AM

Links full text

openaccess

Identifiers

Collections

UNIV-ORLEANS | MSL | MSL-THESE | PRISME-CVL | INSA-GROUPE | INSA-CVL

Citation

Rima Touahria, Abdenour Hacine-Gharbi, Philippe Ravier. Discrete Wavelet based Features for PCG Signal Classification using Hidden Markov Models. 10th International Conference on Pattern Recognition Applications and Methods, Feb 2021, Online Streaming, Austria. pp.334-340, ⟨10.5220/0010343003340340⟩. ⟨hal-03520136⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Les métriques sont temporairement indisponibles