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- W2394056889 abstract "Detecting the presence of chaos from deterministic time series in various fields,such as economics and biology,remains an exciting challenge.A common practice in chaotic time series analysis is to reconstruct an attractor in phase space by utilizing the delay embedding technique,that is,given a scalar time series,the attractor of an(unknown) underlying dynamical system can be reconstructed by unfolding the time series to a higher dimensional time series according to Taken's theorem of embedding.In contrast to conventional reconstruction technique,where the time series of only a single variable of the unknown system is available for the reconstruction and characterization of an attractor,in this paper we present a new technique to perform meaningful reconstruction in the phase space using multidimensional data.To demonstrate the efficiency of our technique,we reconstructed chaotic attractors from multidimensional time series of several existing chaotic systems,such as the Lorenz system,Chen system,Rssler system,Robinovich-fabrikant system and Rssler-hyperchaos system.The results show that the large Lyapunov exponent is more accurate than that estimated from using conventional embedding methods.Even in the cases of non-chaotic and additive noise chaotic systems,our reconstruction technique can perform well." @default.
- W2394056889 created "2016-06-24" @default.
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- W2394056889 date "2009-01-01" @default.
- W2394056889 modified "2023-09-25" @default.
- W2394056889 title "A Reconstruction Technique for Multidimensional Chaotic Time Series" @default.
- W2394056889 hasPublicationYear "2009" @default.
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