Abstract

The Empirical Mode Decomposition (EMD) package contains Python (>=3.5) functions for analysis of non-linear and non-stationary oscillatory time series.

EMD implements a family of sifting algorithms, instantaneous frequency transformations, power spectrum construction and single-cycle feature analysis.

These implementations are supported by online documentation containing a range of practical tutorials.

Citations

Andrew J. Quinn, Vitor Lopes-dos-Santos , David Dupret , Anna Christina Nobre, and Mark W. Woolrich. EMD: Empirical Mode Decomposition and Hilbert-Huang Spectral Analyses in Python. Journal of Open Source Software 6(59), 2977. 31 March 2021

Sponsorship: Supported by the NIHR

DOI: https://doi.org/10.21105/joss.02977

URI: https://www.oxfordhealth.nhs.uk/orka/title/emd-empirical-mode-decomposition-and-hilbert-huang-spectral-analyses-in-python/