Noise-Assisted EMD Methods in Action

In this work we explore the capabilities of two noise-assisted EMD methods: Ensemble EMD (EEMD) and the recently proposed Complete Ensemble EMD with Adaptive Noise (CEEMDAN), to recover a pure tone embedded in dierent kinds of noise, both stationary and nonstationary. Experiments are carried out for...

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Detalles Bibliográficos
Autores: Colominas, Marcelo Alejandro, Schlotthauer, Gaston, Torres, Maria Eugenia, Flandrin, Patrick
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2012
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/197442
Acceso en línea:http://hdl.handle.net/11336/197442
Access Level:acceso abierto
Palabra clave:Empirical Mode Decomposition
Ensemble Empirical Mode Decomposition
Complete Ensemble Empirical Mode Decomposition with Adaptive Noise
Adaptive Signal Processing
https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
Descripción
Sumario:In this work we explore the capabilities of two noise-assisted EMD methods: Ensemble EMD (EEMD) and the recently proposed Complete Ensemble EMD with Adaptive Noise (CEEMDAN), to recover a pure tone embedded in dierent kinds of noise, both stationary and nonstationary. Experiments are carried out for assessing their performances with respect to the level of the added noise and the number of realizations used for averaging. The obtained results partly support empirical recommendations reported in the literature while evidencing new distinctive features. While EEMD presents quite dierent behaviors for dierent situations, CEEMDAN evidences some robustness with an almost unaected performance for the studied cases.