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
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;
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
DOI :
10.1109/ICCCAS.2006.284648
