[1]杨绿溪,李克,周长春,等.一种用于超高斯和亚高斯混合信号盲分离的新算法[J].东南大学学报(自然科学版),1999,29(1):1-7.[doi:10.3969/j.issn.1001-0505.1999.01.001]
 Yang Luxi,Li Ke,Zhou Changchun,et al.A New Blind Separation Algorithm for Hybrid Mixture of Sub- and Super-Gaussian Signals[J].Journal of Southeast University (Natural Science Edition),1999,29(1):1-7.[doi:10.3969/j.issn.1001-0505.1999.01.001]
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一种用于超高斯和亚高斯混合信号盲分离的新算法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
29
期数:
1999年第1期
页码:
1-7
栏目:
信息与通信工程
出版日期:
1999-01-20

文章信息/Info

Title:
A New Blind Separation Algorithm for Hybrid Mixture of Sub- and Super-Gaussian Signals
作者:
杨绿溪 李克 周长春 何振亚
东南大学无线电工程系, 南京 210096
Author(s):
Yang Luxi Li Ke Zhou Changchun He Zhenya
Department of Radio Engineering, Southeast University, Nanjing 210096
关键词:
信息传输最大化 信号盲分离 超高斯和亚高斯
Keywords:
InfoMax blind source separation super-Gaussian and sub-Gaussian
分类号:
TN911.7
DOI:
10.3969/j.issn.1001-0505.1999.01.001
摘要:
揭示了InfoMax盲源分离算法也是以Kullback-Leibler散度为代价函数的, 它之所以能有效地用于语音盲分离, 是因为所选取的非线性函数的导数能够近似为源信号的概率密度函数(PDF). 由此又提出一种广义非线性InfoMax算法, 该算法在估计分离矩阵的同时也对非线性函数进行迭代估计. 实验结果表明这一算法能有效地分离任何超高斯和亚高斯信号的混合信号, 包括语音、图像信号或其它信号的混合.
Abstract:
In this paper, we show that the InfoMax blind separation algorithm is also based on the contrast function of Kullback-Leibler divergence. Its high separating performance for speech sources is closely related to the fact that the selected nonlinear functions approximate the probability density functions (PDFs) of source signals. With this understanding, we propose a new nonlinear InfoMax algorithm in which the nonlinear functions are iteratively updated simultaneously with the estimation of unmixing matrix. Simulation results show that the algorithm can extract independent sources from the hybrid mixture of any super-Gaussian and sub-Gaussian signals.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目:国家自然科学基金资助项目(69872009).
第一作者:男,1964年生,博士,副教授.
更新日期/Last Update: 1999-01-20