| 一种适用于微弱信号提取的盲源分离算法 |
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| 引用本文： | 理华,侯朝焕,马晓川,杨俊.一种适用于微弱信号提取的盲源分离算法[J].应用声学,2009,28(4):249-253. |
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| 作者姓名： | 理华 侯朝焕 马晓川 杨俊 |
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| 作者单位： | 1. 中国科学院声学研究所,北京,100190;中国科学院研究生院,北京,100039
2. 中国科学院声学研究所,北京,100190 |
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| 摘 要： | 本文首次提出了适用于微弱信号提取的盲源分离算法,这种方法是在常用的自然梯度串行更新算法基础上采用了有监督的机制。通过观察两个信号互相关的程度自动判别激活函数的种类,实现了超高斯亚高斯强弱信号混合下的盲源分离。信号仿真表明,有监督的盲源分离技术收敛速度较快,精度较高。
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| 关 键 词： | 盲源分离 独立分量分析 超高斯 亚高斯 激活函数 |
A blind separation algorithm for weak signal extraction |
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| LI Hu,HOU Chao-Huan,MA Xiao-Chuan and YANG Jun.A blind separation algorithm for weak signal extraction[J].Applied Acoustics,2009,28(4):249-253. |
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| Authors: | LI Hu HOU Chao-Huan MA Xiao-Chuan and YANG Jun |
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| Institution: | 1,2) (1 Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190) (2 Graduate University of Chinese Academy of Sciences,Beijing 100039) |
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| Abstract: | A blind separation algorithm for weak signal extraction is proposed.This algorithm is based on the natural gradient algorithm but in addition supervises the quality of separation to estimate the activation function automatically on noting the correlation of two signals.Mixed super-Gaussian and sub-Gaussian signals of which one is strong and the other is weak are separated successfully.The simulation shows that this algorithm converges relatively precisely and quickly. |
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| Keywords: | Blind separation Independent component analysis Super-gaussian Subgaussian Activation function |
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