A method of estimating the noise level in a chaotic time series

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

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22 Citations (Scopus)

Abstract

An attempt is made in this study to estimate the noise level present in a chaotic time series. This is achieved by employing a linear least-squares method that is based on the correlation integral form obtained by Diks in 1999. The effectiveness of the method is demonstrated using five artificial chaotic time series, the Hénon map, the Lorenz equation, the Duffing equation, the Rossler equation and the Chua's circuit whose dynamical characteristics are known a priori. Different levels of noise are added to the artificial chaotic time series and the estimated results indicate good performance of the proposed method. Finally, the proposed method is applied to estimate the noise level present in some real world data sets. Copyright © 2008 American Institute of Physics.
Original languageEnglish
Article number023115
JournalChaos
Volume18
Issue number2
DOIs
Publication statusPublished - 2008

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Chaotic Time Series
Time series
estimating
Correlation Integral
Lorenz Equations
Duffing Equation
Chua's Circuit
Linear Least Squares
Integral form
least squares method
estimates
Least Square Method
Estimate
Networks (circuits)

Citation

Jayawardena, A. W., Xu, P., & Li, W. K. (2008). A method of estimating the noise level in a chaotic time series. Chaos, 18(2). Retrieved from https://doi.org/10.1063/1.2903757