中国物理B ›› 2007, Vol. 16 ›› Issue (2): 352-358.doi: 10.1088/1009-1963/16/2/014

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Least mean square error difference minimum criterion for adaptive chaotic noise canceller

张家树   

  1. Sichuan Province Key Lab of Signal \& Information Processing, Southwest Jiaotong University, Chengdu 610031, China
  • 收稿日期:2006-05-27 修回日期:2006-09-01 出版日期:2007-02-20 发布日期:2007-02-20
  • 基金资助:
    Supported by the National Natural Science Foundation of China (grant No 60572027), the Program for New Century Excellent Talents in University of China (Grant No NCET-05- 0794), and the National Key Lab. of Anti-jamming Communication Foundation of University of Electronic Science and Technology of China (Grant Nos 51434110104QT2201 and 51435080104QT2201).

Least mean square error difference minimum criterion for adaptive chaotic noise canceller

Zhang Jia-Shu(张家树)†   

  1. Sichuan Province Key Lab of Signal & Information Processing, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2006-05-27 Revised:2006-09-01 Online:2007-02-20 Published:2007-02-20
  • Supported by:
    Supported by the National Natural Science Foundation of China (grant No 60572027), the Program for New Century Excellent Talents in University of China (Grant No NCET-05- 0794), and the National Key Lab. of Anti-jamming Communication Foundation of University of Electronic Science and Technology of China (Grant Nos 51434110104QT2201 and 51435080104QT2201).

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摘要： The least mean square error difference (LMS-ED) minimum criterion for an adaptive chaotic noise canceller is proposed in this paper. Different from traditional least mean square error minimum criterion in which the error is uncorrelated with the input vector, the proposed LMS-ED minimum criterion tries to minimize the correlation between the error difference and input vector difference. The novel adaptive LMS-ED algorithm is then derived to update the weights of adaptive noise canceller. A comparison between cancelling performances of adaptive least mean square (LMS), normalized LMS (NLMS) and proposed LMS-ED algorithms is simulated by using three kinds of chaotic noises. The simulation results clearly show that the proposed algorithm outperforms the LMS and NLMS algorithms in achieving small values of steady-state excess mean square error. Moreover, the computational complexity of the proposed LMS-ED algorithm is the same as that of the standard LMS algorithms.

关键词: chaotic noise, adaptive noise canceller, error difference

Abstract: The least mean square error difference (LMS-ED) minimum criterion for an adaptive chaotic noise canceller is proposed in this paper. Different from traditional least mean square error minimum criterion in which the error is uncorrelated with the input vector, the proposed LMS-ED minimum criterion tries to minimize the correlation between the error difference and input vector difference. The novel adaptive LMS-ED algorithm is then derived to update the weights of adaptive noise canceller. A comparison between cancelling performances of adaptive least mean square (LMS), normalized LMS (NLMS) and proposed LMS-ED algorithms is simulated by using three kinds of chaotic noises. The simulation results clearly show that the proposed algorithm outperforms the LMS and NLMS algorithms in achieving small values of steady-state excess mean square error. Moreover, the computational complexity of the proposed LMS-ED algorithm is the same as that of the standard LMS algorithms.

Key words: chaotic noise, adaptive noise canceller, error difference

中图分类号:  (Noise: its effects and control)

  • 43.50.-x
02.70.Rr (General statistical methods) 05.45.-a (Nonlinear dynamics and chaos)