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Improved complete ensemble EMD: A suitable tool for biomedical signal processing

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Colominas, Marcelo A., Schlotthauer, Gastón, Torres, María E.·2014·Biomedical Signal Processing and Control

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Research works printed but not linked: 14

  1. Huang, 1998, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proc. R. Soc. Lond. A, 454, 903, 10.1098/rspa.1998.0193 · DOI · Paper page
  2. Wu, 2009, Ensemble empirical mode decomposition: a noise-assisted data analysis method, Adv. Adapt. Data Anal., 1, 1, 10.1142/S1793536909000047 · DOI · Paper page
  3. Flandrin, 2004, Empirical mode decomposition as a filter bank, IEEE Signal Process. Lett., 11, 112, 10.1109/LSP.2003.821662 · DOI · Paper page
  4. Lei, 2009, Application of the EEMD method to rotor fault diagnosis of rotating machinery, Mech. Syst. Signal Process., 23, 1327, 10.1016/j.ymssp.2008.11.005 · DOI · Paper page
  5. Wu, 2008, The modulated annual cycle: an alternative reference frame for climate anomalies, Clim. Dyn., 31, 823, 10.1007/s00382-008-0437-z · DOI
  6. Yeh, 2010, Complementary ensemble empirical mode decomposition: a novel noise enhanced data analysis method, Adv. Adap. Data Anal., 2, 135, 10.1142/S1793536910000422 · DOI · Paper page
  7. Han, 2013, Empirical mode decomposition for seismic time–frequency analysis, Geophysics, 78, O9, 10.1190/geo2012-0199.1 · doi:10.1190/geo2012-0199.1
  8. Colominas, 2012, Noise-assisted EMD methods in action, Adv. Adapt. Data Anal., 04, 1250025, 10.1142/S1793536912500252 · DOI · Paper page
  9. Henrich, 2004, On the use of the derivative of electroglottographic signals for characterization of nonpathological phonation, J. Acoust. Soc. Am., 115, 1321, 10.1121/1.1646401 · DOI · Paper page
  10. Amann, 2005, Reliability of old and new ventricular fibrillation detection algorithms for automated external defibrillators, BioMed. Eng. Online, 4
  11. Amann, 2007, Detecting ventricular fibrillation by time-delay methods, IEEE Trans. Biomed. Eng., 54, 174, 10.1109/TBME.2006.880909 · doi:10.1109/tbme.2006.880909
  12. Ocak, 2009, Automatic detection of epileptic seizures in EEG using discrete wavelet transform and approximate entropy, Expert Syst. Appl., 36, 2027, 10.1016/j.eswa.2007.12.065 · DOI · Paper page
  13. Añino, 2003, Slight parameter changes detection in biological models: a multiresolution approach, Phys. A: Stat. Mech. Appl., 324, 645, 10.1016/S0378-4371(03)00025-6 · doi:10.1016/s0378-4371(03)00025-6
  14. Torres, 2003, Automatic detection of slight parameter changes associated to complex biomedical signals using multiresolution q-entropy, Med. Eng. Phys., 25, 859, 10.1016/S1350-4533(03)00080-8 · doi:10.1016/s1350-4533(03)00080-8

Metadata

Authors
Colominas, M. A., Schlotthauer, G., & Torres, M. E.
Venue
Biomedical Signal Processing and Control
Publisher
Elsevier BV
Published
2014-11
Volume
14
Pages
19-29
ISSN
1746-8094 (ISSN-L)
OpenAlex
W2009465763
Cited by
1,471
References
0
FWCI
44.29
Type
journal article
Language
en
Open access
bronze
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Funders
  • Argentine National Agency for Scientific and Technological Promotion
  • Universidad Nacional de Entre Ríos (Argentina)
  • Argentine National Scientic and Technical Research Council

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CoChat. (2026). Citation check: Improved complete ensemble EMD: A suitable tool for biomedical signal processing. https://app.cochat.ai/papers/10.1016/j.bspc.2014.06.009
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Colominas, M. A., Schlotthauer, G., & Torres, M. E. (2014). Improved complete ensemble EMD: A suitable tool for biomedical signal processing. Biomedical Signal Processing and Control. https://doi.org/10.1016/j.bspc.2014.06.009

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.