| 基于独立分量分析的噪声消除技术 |
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| 引用本文： | 范乐昊,邱晓晖,司海飞. 基于独立分量分析的噪声消除技术[J]. 金陵科技学院学报, 2006, 22(4): 45-48 |
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| 作者姓名： | 范乐昊 邱晓晖 司海飞 |
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| 作者单位： | 南京邮电大学通信与信息工程学院,江苏,南京,210003;金陵科技学院机电工程学院,江苏,南京,210001 |
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| 摘 要： | 通过分析传统去噪方法的优缺点,引入基于独立分量分析的噪声消除方法,该方法不需要观测信号为确定性信号的前提假设,通过对加噪观测信号进行盲源分离,得到源观测信号,从而实现对噪声的消除。仿真结果证明基于独立分量分析的噪声消除方法,有效地去除了观测信号中的加性噪声。
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| 关 键 词： | 独立分量分析 盲源分离 去噪 |
| 文章编号： | 1672-755X(2006)04-0045-04 |
| 修稿时间： | 2006-05-21 |
The Technology of De-nosing Based on Independent Component Analysis |
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| FAN Le-hao,QIU Xiao-hui,SI Hai-fei. The Technology of De-nosing Based on Independent Component Analysis[J]. Journal of Jinling Institute of Technology, 2006, 22(4): 45-48 |
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| Authors: | FAN Le-hao QIU Xiao-hui SI Hai-fei |
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| Abstract: | On analyzing traditional de-noising methods at their characteristics,a new method based on independent component analysis(ICA) was applied.According to the principle of maximizing statistical independence between the estimated components formulated by high order accumulates,the blind source separation(BSS) of ICA was applied to the extended observed signal.Thus,the virtual sources were extracted one by one,and the noise embedded in the observed signal was removed.Simulations show the additive noise is removed efficiently from observed signal applied this method. |
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| Keywords: | independent component analysis(ICA) blind source separation(BSS) de-nosing |
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