- Base functions for estimating the entropy of a single univariate time series.
- Cross functions for estimating the entropy between two univariate time series.
- Multivariate functions for estimating the entropy of a multivariate dataset.
- Bidimensional functions for estimating the entropy of a two-dimensional univariate matrix.
- Multiscale functions for estimating the multiscale entropy of a single univariate time series using any of the Base entropy functions.
- Multiscale Cross functions for estimating the multiscale entropy between two univariate time series using any of the Cross-entropy functions.
- Multivariate Multiscale functions for estimating the multivariate multiscale entropy of multivariate dataset using any of the Multivariate-entropy functions.
- Other Supplementary functions for various tasks related to EntropyHub and signal processing.
인용 양식
Flood, Matthew W., and Bernd Grimm. “EntropyHub: An Open-Source Toolkit for Entropic Time Series Analysis.” PLOS ONE, edited by Mashallah Rezakazemi, vol. 16, no. 11, Public Library of Science (PLoS), Nov. 2021, p. e0259448, doi:10.1371/journal.pone.0259448.
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버전 | 게시됨 | 릴리스 정보 | |
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2.0.0.1 | + Multivariate Sample Entropy
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2.0 | + Multivariate Sample Entropy
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1.0 | New Functions (RangEn, DivEn)
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0.2.1 | License and Terms of Use updated to comply with MatLab File Exchange policies. |
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0.2 | The update to v0.2 includes two new bidimensional entropy functions: Bidimensional Permutation Entropy (PermEn2D)
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0.1.1 | The update to v0.1.1 includes a correction to the EnofEn function, allowing the user to specify the signal range (xmin, xmax) as outlined in the source literature. Other updates relate to documentation. |
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0.1 |
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