Blind source separation without permutation and scaling indeterminacy

被引：0
|
作者：
Ishibashi, T [1 ]
Inoue, K [1 ]
Koya, T [1 ]
Gotanda, H [1 ]
Kumamaru, K [1 ]
机构：
[1] Kyushu Inst Technol, Fac Comp Sci & Syst Engn, Iizuka, Fukuoka 8208502, Japan
来源：
SICE 2004 ANNUAL CONFERENCE, VOLS 1-3 | 2004年
关键词：
blind source separation; frequency domain ICA; scaling and permutation problem; noise reduction; target source extraction;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Independent component analysis (ICA) can separate unknown sources using only their mixtures if they axe statistically independent. However, the scaling and permutation problem occur at each frequency when the frequency domain ICA is adopted; it is essential to solve this problem peculiar to ICA. In the present paper, a permutation correction rule is proposed by using locational information on the sources under a multi-source and multi-microphone configuration. A method for extracting human speech exclusively is also proposed.
引用
收藏
页码：2298 / 2301
页数：4
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