Introducing \texttt{libeemd}: a program package for performing the ensemble empirical mode decomposition
type: Item
instance of: scholarly article
title: Introducing \texttt{libeemd}: a program package for performing the ensemble empirical mode decomposition
zbMATH Open document ID: 1342.65045
author: P. J. J. Luukko
author: E. Räsänen
author: Jouni Helske
published in: Computational Statistics
publication date: 2016-08-04T00:00:00Z
full work available at URL: https://arxiv.org/abs/1707.00487
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 62-04
Mathematics Subject Classification ID: 62M10
zbMATH DE Number: 6609285
zbMATH Keywords: Hilbert-Huang transform
zbMATH Keywords: intrinsic mode function
zbMATH Keywords: time series analysis
zbMATH Keywords: adaptive data analysis
zbMATH Keywords: noise-assisted data analysis
zbMATH Keywords: detrending
Wikidata QID: Q62444160
describes a project that uses: hht
describes a project that uses: Rcpp
describes a project that uses: R
describes a project that uses: EMD
describes a project that uses: GSL
describes a project that uses: Python
MaRDI profile type: Publication
OpenAlex ID: W3099618244
arXiv ID: 1707.00487
cites work: A B-spline approach for empirical mode decompositions
cites work: Seamless R and C++ Integration with Rcpp
cites work: Q4891492
cites work: Speech pitch determination based on Hilbert-Huang transform
cites work: Q3375593
cites work: A confidence limit for the empirical mode decomposition and Hilbert spectral analysis
cites work: The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
cites work: A study of the characteristics of white noise using the empirical mode decomposition method
DOI: 10.1007/S00180-015-0603-9
description: scientific article