Title
Modeling Of Chaotic Systems With Multiwavelet Transform Combined With Recurrent Least Squares Support Vector Machines
Abstract
A new algorithm for modeling of chaotic systems is presented in this paper. First, more information is acquired utilizing the reconstructed embedding phase space, and the multiwavelets transform provides a sensible decomposition of the data so that the underlying temporal structures of the original time series become more tractable. Second, based on the Recurrent Least Squares Support Vector Machines (RLS-SVM), modeling of the chaotic system is realized. To demonstrate the effectiveness of our algorithm, we use the power spectrum and dynamic invariants involving the Lyapunov exponents and the correlation dimension as criterions, and then apply our method to Chua's circuit time series. The similarity of dynamic invariants between the original and generated time series shows that the proposed method can capture the dynamics of the chaotic time series more effectively.
Year
DOI
Venue
2007
10.1142/S0219691307001628
INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING
Keywords
DocType
Volume
multiwavelet, phase space, chaotic attractor, support vector machines
Journal
5
Issue
ISSN
Citations 
1
0219-6913
0
PageRank 
References 
Authors
0.34
5
3
Name
Order
Citations
PageRank
Zheng Xiang100.34
Taiyi Zhang217617.60
Jiancheng Sun3437.79