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author:

Xiang, Xiaodong (Xiang, Xiaodong.) [1] (Scholars:向小东)

Indexed by:

EI Scopus

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. ©2009 IEEE.

Keyword:

Least squares approximations Noise abatement Support vector machines Time series

Community:

  • [ 1 ] [Xiang, Xiaodong]School of Management, Fuzhou University, Fuzhou, Fujian 350108, China

Reprint 's Address:

  • 向小东

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Year: 2009

Language: English

Cited Count:

WoS CC Cited Count:

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ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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