DocumentCode
460398
Title
Noise Reduction of Chaotic Systems Based on Least Squares Support Vector Machines
Author
Sun, Jiancheng ; Zhou, Yatong
Author_Institution
Dept. of Commun. Eng., Jiangxi Univ. of Finance & Econ., Nanchang
Volume
1
fYear
2006
fDate
25-28 June 2006
Firstpage
336
Lastpage
339
Abstract
In order to resolve the noise reduction in chaotic system, a novel idea based on least square support vector machine (LS-SVM) is proposed in this paper. By analyzing the relationship between the function approximation and the noise reduction, we realized that the noise reduction can be implemented by the function approximation techniques. On the basis of the LS-SVM, the function approximation is carried out and the noise reduction achieved simultaneously
Keywords
chaos; function approximation; learning (artificial intelligence); least squares approximations; noise; nonlinear dynamical systems; support vector machines; LS-SVM; chaotic system; function approximation; least square support vector machine; noise reduction; Chaos; Chaotic communication; Finance; Function approximation; Least squares approximation; Least squares methods; Multidimensional systems; Noise reduction; Shadow mapping; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, Circuits and Systems Proceedings, 2006 International Conference on
Conference_Location
Guilin
Print_ISBN
0-7803-9584-0
Electronic_ISBN
0-7803-9585-9
Type
conf
DOI
10.1109/ICCCAS.2006.284648
Filename
4063892
Link To Document