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.
Similar content
Hippocampal Ripple Diversity organises Neuronal Reactivation Dynamics in the Offline Brain
A mechanism for hippocampal memory recall based on excitatory-inhibitory fluctuations in neocortex
Organizing the coactivity structure of the hippocampus from robust to flexible memory
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.
Citation
DOI
Downloads