On the use of time-frequency representation in multicomponent signal separation

被引:0
|
作者
Barkat, Braham
Sattar, Farook
Abed-Meraim, Karim
机构
[1] Acad Directorate, Petroleum Inst, Elect Engn Program, Abu Dhabi, U Arab Emirates
[2] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[3] Telecom Paris, Signal & Image Processing Dept, Paris, France
关键词
D O I
10.1109/ICME.2006.262716
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we address the problem of separating unknown multicomponent signals from their instantaneous mixtures. Using linear time-frequency (TF) representation of the mixtures along with vectors classification scheme provide us a simple and efficient technique to separate multicomponent signals. The proposed algorithm can handle monocomponent as well as multicomponent sources and its assumptions about the mixing matrix are more relaxed compared to other existing TF based algorithms. The source separation results for the mixed synthetic signals as well as mixed real audio signals, such as mixture of speech and music, are shown to illustrate the validity and efficiency of the proposed scheme.
引用
收藏
页码:1057 / 1060
页数:4
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