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Empirical Mode Decomposition as a Filter Bank
Abstract
Empirical mode decomposition (EMD) has recently been pioneered by Huang et al. for adaptively representing nonstationary signals as sums of zero-mean amplitude modulation frequency modulation components. In order to better understand the way EMD behaves in stochastic situations involving broadband noise, we report here on numerical experiments based on fractional Gaussian noise. In such a case, it turns out that EMD acts essentially as a dyadic filter bank resembling those involved in wavelet decompositions. It is also pointed out that the hierarchy of the extracted modes may be similarly exploited for getting access to the Hurst exponent.
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Cited by
A complete ensemble empirical mode decomposition with adaptive noise
Torres, M. E., Colominas, M. A., Schlotthauer, G., & Flandrin, P. (2011) · 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp.2011.5947265 · Cited by 2,801
Self-citationGilles, J. (2013) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2013.2265222 · Cited by 2,210
Enabling Health Monitoring Approach Based on Vibration Data for Accurate Prognostics
Javed, K., Gouriveau, R., Zerhouni, N., & Nectoux, P. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2014.2327917 · Cited by 351
EEMD method and WNN for fault diagnosis of locomotive roller bearings
Lei, Y., He, Z., & Zi, Y. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2010.12.095 · Cited by 316
Petrantonakis, P. C., & Hadjileontiadis, L. J. (2010) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2010.7 · Cited by 260
Metadata
- Authors
- Flandrin, P., Rilling, G., & Goncalves, P.
- Venue
- IEEE Signal Processing Letters
- Published
- 2004-02
- Volume
- 11
- Issue
- 2
- Pages
- 112-114
- ISSN
- 1070-9908 (ISSN-L)
- OpenAlex
- W2098395403
- Cited by
- 2,583
- References
- 0
- FWCI
- 93.81
- Type
- journal article
- Language
- en
- Open access
- closed
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