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Godwin H

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Posts tagged time-serie

Empirical Mode Decomposition

  • 06 May 2021
  • Machine Learning
  • machine-learning time-serie data-decomposition signal-processing

Introduced by Hilbert–Huang, Empirical Mode Decomposition (EMD) is a data-driven method that used as a propelling tool for analyzing and decomposing non-stationary and non-linear data. EMD generates a finite and often small number of the frequency and amplitude modulated signals, intrinsic mode functions (IMF).

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