Please use this identifier to cite or link to this item:
Title: Detecting chaos from time series
Authors: Xiaofeng, G. 
Lai, C.H. 
Issue Date: 11-Feb-2000
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.
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.
Source Title: Journal of Physics A: Mathematical and General
ISSN: 03054470
DOI: 10.1088/0305-4470/33/5/313
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Feb 14, 2020

Page view(s)

checked on Feb 16, 2020

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.