Multiple Sparse Sources Separation Based on Multichannel Frequency Domain Adaptive Filtering
óUnderdetermined sparse sources separation is a challenge problem especially in adverse environment, where there are often some non-sparse interferences or more than one sparse interferences located closely to the target sources. While in some applications, such as in-car or hands-free environments, references of the interferences (P 2) coming from loudspeakers are available. Common sparse source separation approaches have not yet used these reference information, we call them traditional approaches in this paper. We propose a FD-MENUET (Frequency domain aDaptive ltering based Multiple sENsor degenerate Unmixing Estimation Technique) approach, in which we get full use of those reference information to help to separate the target sources. Even if no reference is available, the approach would only degenerate to the traditional approaches. The experimental results show that the proposed approach is more general and could achieves better separation performance than the traditional one.
Xiaoyu CHEN Zhong-hua FU Lei XIE
Shaanxi Provincial Key Laboratory of Speech and Image Information Processing, Northwestern Polytechn Shaanxi Provincial Key Laboratory of Speech and Image Information Processing,Northwestern Polytechni
国际会议
2011亚太信号与信息处理协会年度峰会(APSIPAASC 2011)
西安
英文
1-5
2011-10-18（万方平台首次上网日期，不代表论文的发表时间）