EMD: Empirical Mode Decomposition and Hilbert-Huang Spectral Analyses in Python.

Autor: Quinn AJ; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK., Lopes-Dos-Santos V; Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX1 3TH, United Kingdom., Dupret D; Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX1 3TH, United Kingdom., Nobre AC; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK.; Department of Experimental Psychology, University of Oxford, Oxford, OX2 6GG, UK., Woolrich MW; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK.
Jazyk: angličtina
Zdroj: Journal of open source software [J Open Source Softw] 2021 Mar 31; Vol. 6 (59).
DOI: 10.21105/joss.02977
Abstrakt: 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.
Databáze: MEDLINE