EMD: Empirical Mode Decomposition and Hilbert-Huang Spectral Analyses in Python
Scientific 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.
A segment of the LFP recording separated into six intrinsic mode functions using a masked empirical mode decomposition. The theta oscillation is isolated into IMF 6.
Citation
Journal of Open Source Software, 6(59), 2977.
DOI
10.21105/joss.02977
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