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|a 10.21105/joss.02977
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|a eng
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1 |
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|a Quinn, Andrew J
|e verfasserin
|4 aut
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|a EMD
|b Empirical Mode Decomposition and Hilbert-Huang Spectral Analyses in Python
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|c 2021
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Revised 10.03.2022
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a 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
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|a Journal Article
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|a Lopes-Dos-Santos, Vitor
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Dupret, David
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Nobre, Anna Christina
|e verfasserin
|4 aut
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| 700 |
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|a Woolrich, Mark W
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Journal of open source software
|d 2017
|g 6(2021), 59 vom: 31. März
|w (DE-627)NLM275088057
|x 2475-9066
|7 nnns
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| 773 |
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|g volume:6
|g year:2021
|g number:59
|g day:31
|g month:03
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|u http://dx.doi.org/10.21105/joss.02977
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