Published June 1, 2009
| Version v1
Journal article
Chaotic time series prediction: From one to another
Creators
- 1. College of Mathematics, Jilin University, Changchun 130012 (China)
- 2. College of Basic Sciences, Changchun University of Technology, Changchun 130012 (China)
- 3. College of Computer Science and Technology, Jilin University, Changchun 130012 (China)
Description
In this Letter, a new local linear prediction model is proposed to predict a chaotic time series of a component x(t) by using the chaotic time series of another component y(t) in the same system with x(t). Our approach is based on the phase space reconstruction coming from the Takens embedding theorem. To illustrate our results, we present an example of Lorenz system and compare with the performance of the original local linear prediction model.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.physleta.2009.04.033Additional details
Identifiers
- DOI
- 10.1016/j.physleta.2009.04.033;
- PII
- S0375-9601(09)00507-6;
Publishing Information
- Journal Title
- Physics Letters. A
- Journal Volume
- 373
- Journal Issue
- 25
- Journal Page Range
- p. 2174-2177
- ISSN
- 0375-9601
- CODEN
- PYLAAG
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 41059591
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
- Descriptors DEI
- CHAOS THEORY; COMPARATIVE EVALUATIONS; FORECASTING; PERFORMANCE; PHASE SPACE; TIME-SERIES ANALYSIS
- Descriptors DEC
- EVALUATION; MATHEMATICAL SPACE; MATHEMATICS; SPACE; STATISTICS
Optional Information
- Copyright
- Copyright (c) 2009 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.