Time series prediction using Lyapunov exponents in embedding phase space
- Authors
- Zhang, Jun; Lam, Ka Chi; Yan, Wen Jun; Gao, Hang; Li, Yuan
- Issue Date
- Jan-2004
- Publisher
- Pergamon Press Ltd.
- Citation
- Computers and Electrical Engineering, v.30, no.1, pp 1 - 15
- Pages
- 15
- Indexed
- SCIE
SCOPUS
- Journal Title
- Computers and Electrical Engineering
- Volume
- 30
- Number
- 1
- Start Page
- 1
- End Page
- 15
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/115952
- DOI
- 10.1016/S0045-7906(03)00015-6
- ISSN
- 0045-7906
1879-0755
- Abstract
- This paper describes a novel method of chaotic time series prediction, which is based on the fundamental characteristic of chaotic behavior that sensitive dependence upon initial conditions (SDUIC), and Lyapunov exponents (LEs) is a measure of the SDUIC in chaotic systems. Because LEs of chaotic time series data provide a quantitative analysis of system dynamics in different embedding dimension after embedding a chaotic time series in different embedding dimension phase spaces, a novel multi-dimension chaotic time series prediction method using LEs is proposed in this paper. This is done by first reconstructing a phase space using chaotic time series, then using LEs as a quantitative parameter to predict an unknown phase space point, after transferring the phase space point to time domain, the predicted chaotic time series data can be obtained. The computer simulation result of simulation showed that the proposed method is simple, practical and effective. (C) 2003 Elsevier Ltd. All rights reserved.
- Files in This Item
-
Go to Link
- Appears in
Collections - COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/115952)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.