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CEEMDAN

Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) er en forbedret variant av empirisk modusdekomponering (EMD) som adresserer artefakter med modus-blanding gjennom ensemble-gjennomsnittsberegning med adaptiv støy. Introdusert av Torres og kolleger (2011), dekomponerer CEEMDAN signaler til iboende modusfunksjoner (IMFs) som representerer svingninger på forskjellige skalaer. Metoden legger til kontrollert støy til flere realisasjoner og gjennomsnittsberegner resultatene, noe som gir mer stabile, fysisk meningsfulle komponenter enn standard EMD.

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  1. Torres, M. E., Colominas, M. A., Schlotthauer, G., & Flandrin, P. (2011). A complete ensemble empirical mode decomposition with adaptive noise. In 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 4144–4147). DOI: 10.1109/ICASSP.2011.5947265
  2. Colominas, M. A., Schlotthauer, G., & Torres, M. E. (2014). Improved complete ensemble empirical mode decomposition with adaptive noise. IEEE Transactions on Signal Processing, 63(6), 1408–1413. link
  3. Huang, N. E., et al. (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society of London A, 454(1971), 903–995. DOI: 10.1098/rspa.1998.0193

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ScholarGate. (2026, June 3). Complete Ensemble Empirical Mode Decomposition with Adaptive Noise. ScholarGate. https://scholargate.app/no/time-series/ceemdan

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ScholarGateCEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise). Hentet 2026-06-15 fra https://scholargate.app/no/time-series/ceemdan · Datasett: https://doi.org/10.5281/zenodo.20539026