Title :
Research on Noise Reduction Method for Chaotic Time Series and Its Application Based on Least Square Support Vector Machine
Author_Institution :
Sch. of Manage., Fuzhou Univ., Fuzhou, China
Abstract :
With regard to the need of non-noise data for the many existing chaos-discerning methods, the noise reduction method for chaotic time series based on least square support vector machine is proposed, followed by specific steps for its application. The result of emulation by Henon reflection system proves the effectiveness of this method.
Keywords :
chaos; least squares approximations; signal denoising; support vector machines; Henon reflection system; chaos-discerning methods; chaotic time series; least square support vector machine; noise reduction method; Acoustic reflection; Chaos; Cognition; Emulation; Least squares methods; Noise reduction; Nonlinear dynamical systems; Shadow mapping; Signal to noise ratio; Support vector machines;
Conference_Titel :
Management and Service Science, 2009. MASS '09. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4638-4
Electronic_ISBN :
978-1-4244-4639-1
DOI :
10.1109/ICMSS.2009.5303374
