Please use this identifier to cite or link to this item:
https://doi.org/10.1088/0305-4470/33/5/313
DC Field | Value | |
---|---|---|
dc.title | Detecting chaos from time series | |
dc.contributor.author | Xiaofeng, G. | |
dc.contributor.author | Lai, C.H. | |
dc.date.accessioned | 2014-10-16T09:20:29Z | |
dc.date.available | 2014-10-16T09:20:29Z | |
dc.date.issued | 2000-02-11 | |
dc.identifier.citation | Xiaofeng, G., Lai, C.H. (2000-02-11). Detecting chaos from time series. Journal of Physics A: Mathematical and General 33 (5) : 1007-1016. ScholarBank@NUS Repository. https://doi.org/10.1088/0305-4470/33/5/313 | |
dc.identifier.issn | 03054470 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/96181 | |
dc.description.abstract | In this paper, an entirely data-based method to detect chaos from the time series is developed by introducing ∈p-neighbour points (the p-steps ∈-neighbour points). We demonstrate that for deterministic chaotic systems, there exists a linear relationship between the logarithm of the average number of ∈p-neighbour points, ln np,∈, and the time step, p. The coefficient can be related to the KS entropy of the system. The effects of the embedding dimension and noise are also discussed. | |
dc.source | Scopus | |
dc.type | Article | |
dc.contributor.department | PHYSICS | |
dc.description.doi | 10.1088/0305-4470/33/5/313 | |
dc.description.sourcetitle | Journal of Physics A: Mathematical and General | |
dc.description.volume | 33 | |
dc.description.issue | 5 | |
dc.description.page | 1007-1016 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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