Application of local polynomial estimation in suppressing strong chaotic noise

doi:10.1088/1674-1056/21/2/020508

中国物理B ›› 2012, Vol. 21 ›› Issue (2): 20508-020508.doi: 10.1088/1674-1056/21/2/020508

苏理云¹,马艳菊¹,李姣军²

收稿日期:2011-08-06 修回日期:2011-09-22 出版日期:2012-01-30 发布日期:2012-01-30
通讯作者: 苏理云,cloudhopping@163.com E-mail:cloudhopping@163.com

Application of local polynomial estimation in suppressing strong chaotic noise

Su Li-Yun(苏理云)^a)^†, Ma Yan-Ju(马艳菊)^a), and Li Jiao-Jun(李姣军)^b)

1. School of Mathematics and Statistics, Chongqing University of Technology, Chongqing 400054, China;
2. School of Electronic Information and Automation, Chongqing University of Technology, Chongqing 400054, China

Received:2011-08-06 Revised:2011-09-22 Online:2012-01-30 Published:2012-01-30
Contact: Su Li-Yun,cloudhopping@163.com E-mail:cloudhopping@163.com
Supported by:
Project supported by the Natural Science Foundation of Chongqing Science & Technology Commission, China (Grant No. CSTC2010BB2310) and the Chongqing Municipal Education Commission Foundation, China (Grant Nos. KJ080614, KJ100810, and KJ100818).

摘要/Abstract

Abstract: In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series are reconstructed to obtain multivariate time series according to Takens delay embedding theorem. Then the chaotic noise is estimated accurately using local polynomial estimation method. After chaotic noise is separated from observation signal, we can get the estimation of the useful signal. This local polynomial estimation method can combine the advantages of local and global law. Finally, it makes the estimation more exactly and we can calculate the formula of mean square error theoretically. The simulation results show that the method is effective for the suppression of strong chaotic noise when the signal to interference ratio is low.

Key words: strong chaotic noise, local polynomial estimation, weak signal detection

中图分类号: (Time series analysis)

05.45.Tp

05.45.Pq (Numerical simulations of chaotic systems)

苏理云,马艳菊,李姣军. [J]. 中国物理B, 2012, 21(2): 20508-020508.

Su Li-Yun(苏理云), Ma Yan-Ju(马艳菊), and Li Jiao-Jun(李姣军) . Application of local polynomial estimation in suppressing strong chaotic noise[J]. Chin. Phys. B, 2012, 21(2): 20508-020508.

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Application of local polynomial estimation in suppressing strong chaotic noise

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