UNSPECIFIED (1993) DETECTING CHAOS IN A NOISY TIME-SERIES. PROCEEDINGS OF THE ROYAL SOCIETY OF LONDON SERIES B-BIOLOGICAL SCIENCES, 253 (1338). pp. 239-244. ISSN 0962-8452

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Abstract

We propose a new method for detecting low-dimensional chaotic time series when there is dynamical noise present. The method identifies the sign of the largest Liapunov exponent and thus the presence or absence of chaos. It also shows when it is possible to assign a value to the exponent. This approach can work for short time series of only 500 points. We analyse several real time series including chickenpox and measles data from New York City. For model systems it correctly identifies important spatial scales at which noise and nonlinear effects are important. We propose a further technique for estimating the level of noise in real time series if it is difficult to detect by the former method.

Item Type:	Journal Article
Subjects:	Q Science > QH Natural history > QH301 Biology
Journal or Publication Title:	PROCEEDINGS OF THE ROYAL SOCIETY OF LONDON SERIES B-BIOLOGICAL SCIENCES
Publisher:	ROYAL SOC LONDON
ISSN:	0962-8452
Date:	22 September 1993
Volume:	253
Number:	1338
Number of Pages:	6
Page Range:	pp. 239-244
Publication Status:	Published
URI:	http://wrap.warwick.ac.uk/id/eprint/21062

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