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Introducing libeemd: a program package for performing the ensemble empirical mode decomposition
Univ Jyvaskyla, Finland.ORCID iD: 0000-0003-3786-9685
Univ Jyvaskyla, Finland.ORCID iD: 0000-0001-7130-793X
Tampere Univ Technol, Finland.
2016 (English)In: Computational statistics (Zeitschrift), ISSN 0943-4062, E-ISSN 1613-9658, Vol. 31, no 2, p. 545-557Article in journal (Refereed) Published
Abstract [en]

The ensemble empirical mode decomposition (EEMD) and its complete variant (CEEMDAN) are adaptive, noise-assisted data analysis methods that improve on the ordinary empirical mode decomposition (EMD). All these methods decompose possibly nonlinear and/or nonstationary time series data into a finite amount of components separated by instantaneous frequencies. This decomposition provides a powerful method to look into the different processes behind a given time series data, and provides a way to separate short time-scale events from a general trend. We present a free software implementation of EMD, EEMD and CEEMDAN and give an overview of the EMD methodology and the algorithms used in the decomposition. We release our implementation, libeemd, with the aim of providing a user-friendly, fast, stable, well-documented and easily extensible EEMD library for anyone interested in using (E)EMD in the analysis of time series data. While written in C for numerical efficiency, our implementation includes interfaces to the Python and R languages, and interfaces to other languages are straightforward.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2016. Vol. 31, no 2, p. 545-557
Keyword [en]
Hilbert-Huang transform; Intrinsic mode function; Time series analysis; Adaptive data analysis; Noise-assisted data analysis; Detrending
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-144918DOI: 10.1007/s00180-015-0603-9ISI: 000374375800008OAI: oai:DiVA.org:liu-144918DiVA: diva2:1180685
Note

Funding Agencies|Finnish Cultural Foundation; Emil Aaltonen Foundation; Academy of Finland; European Communitys FP7 through the CRONOS project [280879]

Available from: 2018-02-06 Created: 2018-02-06 Last updated: 2018-02-06

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Helske, Jouni

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