Chin. Phys. B ›› 2014, Vol. 23 ›› Issue (1): 10506-010506.doi: 10.1088/1674-1056/23/1/010506

• GENERAL • 上一篇    下一篇

Gradient method for blind chaotic signal separation based on proliferation exponent

吕善翔, 王兆山, 胡志辉, 冯久超   

  1. School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China
  • 收稿日期:2013-06-13 修回日期:2013-07-24 出版日期:2013-11-12 发布日期:2013-11-12
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant No. 60872123), the Joint Fund of the National Natural Science Foundation and the Natural Science Foundation of Guangdong Province, China (Grant No. U0835001), the Fundamental Research Funds for the Central Universities of China (Grant No. 2012ZM0025), the South China University of Technology, China, and the Fund for Higher-Level Talents in Guangdong Province, China (Grant No. N9101070).

Gradient method for blind chaotic signal separation based on proliferation exponent

Lü Shan-Xiang (吕善翔), Wang Zhao-Shan (王兆山), Hu Zhi-Hui (胡志辉), Feng Jiu-Chao (冯久超)   

  1. School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China
  • Received:2013-06-13 Revised:2013-07-24 Online:2013-11-12 Published:2013-11-12
  • Contact: Feng Jiu-Chao E-mail:fengjc@scut.edu.cn
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant No. 60872123), the Joint Fund of the National Natural Science Foundation and the Natural Science Foundation of Guangdong Province, China (Grant No. U0835001), the Fundamental Research Funds for the Central Universities of China (Grant No. 2012ZM0025), the South China University of Technology, China, and the Fund for Higher-Level Talents in Guangdong Province, China (Grant No. N9101070).

摘要: A new method to perform blind separation of chaotic signals is articulated in this paper, which takes advantage of the underlying features in the phase space for identifying various chaotic sources. Without incorporating any prior information about the source equations, the proposed algorithm can not only separate the mixed signals in just a few iterations, but also outperforms the fast independent component analysis (FastICA) method when noise contamination is considerable.

关键词: blind separation, chaotic signals, phase space

Abstract: A new method to perform blind separation of chaotic signals is articulated in this paper, which takes advantage of the underlying features in the phase space for identifying various chaotic sources. Without incorporating any prior information about the source equations, the proposed algorithm can not only separate the mixed signals in just a few iterations, but also outperforms the fast independent component analysis (FastICA) method when noise contamination is considerable.

Key words: blind separation, chaotic signals, phase space

中图分类号:  (Nonlinear dynamics and chaos)

  • 05.45.-a
05.40.Ca (Noise) 05.45.Vx (Communication using chaos)