Particle filtering based noisy blind source separation

被引：2
|
作者：
Cong, F.
Xu, X.
Zhou, S.
Du, S.
Shi, X.
机构：
[1] Shanghai Jiao Tong Univ, State Key Lab Vibrat Shock & Noise, Shanghai 200240, Peoples R China
[2] Hangzhou Appl Acoust Res Inst, State Key Lab Ocean Acoust, Hangzhou 310012, Peoples R China
来源：
ELECTRONICS LETTERS | 2007年 / 43卷 / 09期
关键词：
6;
D O I：
10.1049/el:20070304
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Noisy blind source separation (BSS) is studied. The proposed method mainly consists of two stages. The first step is to enhance each mixture by particle filtering so that (as in the theory) the noisy mixtures become noise-free. The second is to extract the sources by BSS algorithms. For particle filtering, the state-space model is defined by the time-varying autoregressive model of each mixture, and the measured space is set by each observed noisy mixture. Various simulations prove that the approach is effective.
引用
收藏
页码：547 / 549
页数：3
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