Library Header Image
LSE Research Online LSE Library Services

Distinguishing between low-dimensional dynamics and randomness in measured time series

Provenzale, A., Smith, Leonard A., Vio, R. and Murante, G. (1992) Distinguishing between low-dimensional dynamics and randomness in measured time series. Physica D: Nonlinear Phenomena, 58 (1-4). pp. 31-49. ISSN 0167-2789

Full text not available from this repository.
Identification Number: 10.1016/0167-2789(92)90100-2


The success of current attempts to distinguish between low-dimensional chaos and random behavior in a time series of observations is considered. First we discuss stationary stochastic processes which produce finite numerical estimates of the correlation dimension and K2 entropy under naive application of correlation integral methods. We then consider several straightforward tests to evaluate whether correlation integral methods reflect the global geometry or the local fractal structure of the trajectory. This determines whether the methods are applicable to a given series; if they are we evaluate the significance of a particular result, for example, by considering the results of the analysis of stochastic signals with statistical properties similar to those of observed series. From the examples considered, it is clear that the correlation integral should not be used in isolation, but as one of a collection of tools to distinguish chaos from stochasticity.

Item Type: Article
Official URL:
Additional Information: © 1992 Elsevier Science B.V.
Divisions: Centre for Analysis of Time Series
Subjects: Q Science > QA Mathematics
Q Science > QC Physics
Date Deposited: 26 Jan 2009 15:19
Last Modified: 15 May 2024 23:32

Actions (login required)

View Item View Item