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Improved Permutation Entropy for Measuring Complexity of Time Series under Noisy Condition
Joint Authors
Chen, Zhe
Li, Yaan
Liang, Hongtao
Yu, Jing
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-11
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Measuring complexity of observed time series plays an important role for understanding the characteristics of the system under study.
Permutation entropy (PE) is a powerful tool for complexity analysis, but it has some limitations.
For example, the amplitude information is discarded; the equalities (i.e., equal values in the analysed signal) are not properly dealt with; and the performance under noisy condition remains to be improved.
In this paper, the improved permutation entropy (IPE) is proposed.
The presented method combines some advantages of previous modifications of PE.
Its effectiveness is validated through both synthetic and experimental analyses.
Compared with PE, IPE is capable of detecting spiky features and correctly differentiating heart rate variability (HRV) signals.
Moreover, it performs better under noisy condition.
Ship classification experiment results demonstrate that IPE achieves 28.66% higher recognition rate than PE at 0dB.
Hence, IPE could be used as an alternative of PE for analysing time series under noisy condition.
American Psychological Association (APA)
Chen, Zhe& Li, Yaan& Liang, Hongtao& Yu, Jing. 2019. Improved Permutation Entropy for Measuring Complexity of Time Series under Noisy Condition. Complexity،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1131001
Modern Language Association (MLA)
Chen, Zhe…[et al.]. Improved Permutation Entropy for Measuring Complexity of Time Series under Noisy Condition. Complexity No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1131001
American Medical Association (AMA)
Chen, Zhe& Li, Yaan& Liang, Hongtao& Yu, Jing. Improved Permutation Entropy for Measuring Complexity of Time Series under Noisy Condition. Complexity. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1131001
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1131001