Modified correlation entropy estimation for a noisy chaotic time series

A.W. JAYAWARDENA, Pengcheng XU, Wai Keung LI

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15 Citations (Scopus)

Abstract

A method of estimating the Kolmogorov-Sinai (KS) entropy, herein referred to as the modified correlation entropy, is presented. The method can be applied to both noise-free and noisy chaotic time series. It has been applied to some clean and noisy data sets and the numerical results show that the modified correlation entropy is closer to the KS entropy of the nonlinear system calculated by the Lyapunov spectrum than the general correlation entropy. Moreover, the modified correlation entropy is more robust to noise than the correlation entropy. Copyright © 2010 American Institute of Physics.
Original languageEnglish
Article number023104
JournalChaos
Volume20
Issue number2
DOIs
Publication statusPublished - 2010

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Chaotic Time Series
Time series
Entropy
entropy
Lyapunov Spectrum
Noisy Data
nonlinear systems
Nonlinear systems
estimating
Nonlinear Systems
Numerical Results

Citation

Jayawardena, A. W., Xu, P., & Li, W. K. (2010). Modified correlation entropy estimation for a noisy chaotic time series. Chaos, 20(2). Retrieved from https://doi.org/10.1063/1.3382013