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Title: | EMD: Empirical Mode Decomposition and Hilbert-Huang Spectral Analyses in Python |
Authors: | External author(s) only |
Keywords: | Brain Activity |
Issue Date: | Mar-2021 |
Citation: | 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 |
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. |
Description: | This work is licensed under a Creative Commons Attribution 4.0 International License. |
URI: | https://oxfordhealth-nhs.archive.knowledgearc.net/handle/123456789/808 |
Appears in Collections: | Neuroscience |
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