| Least mean square error difference minimum criterion for adaptive chaotic noise canceller |
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| 作者姓名： | 张家树 |
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| 作者单位： | Sichuan Province Key Lab of Signal \& Information Processing, Southwest Jiaotong University, Chengdu 610031, China |
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| 基金项目： | 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.
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| 关 键 词： | 声学 噪音环境 混沌噪声 自适应噪声补偿器 最小均方差最小标准 |
| 收稿时间： | 2006-05-27 |
| 修稿时间： | 9/1/2006 12:00:00 AM |
Least mean square error difference minimum criterion for adaptive chaotic noise canceller |
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| Zhang Jia-Shu.Least mean square error difference minimum criterion for adaptive chaotic noise canceller[J].Chinese Physics B,2007,16(2):352-358. |
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| Authors: | Zhang Jia-Shu |
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| Institution: | Sichuan Province Key Lab of Signal & Information Processing, Southwest Jiaotong University, Chengdu 610031, China |
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| 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. |
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| Keywords: | chaotic noise adaptive
noise canceller error difference |
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