A PARAFAC decomposition based algorithm for blind MIMO source separation

Computational Advances in Multi-Sensor Adaptive Processing(2009)

引用 1|浏览3
暂无评分
摘要
The paper deals with the problem of blind source separation after a MIMO convolutive mixture. We propose an algorithm for the simultaneous extraction of all the sources. It is based on the PARAFAC decomposition of a tensor built from the observations and from so called reference signals. In particular this algorithm allows to overcome the classical drawbacks of the deflation approach in the sequential separation scheme. The order of the PARAFAC decomposition depends on the mixture parameters, the extraction filter length and the number of sources. Then a selection among these PARAFAC factors is proposed, in order to obtain the different sources. A fixed point method improves then the estimation performances iteratively. Computer simulations illustrate the good behavior and the interest of our algorithm in comparison with other approaches.
更多
查看译文
关键词
mimo communication,blind source separation,convolution,mimo convolutive mixture,parafac decomposition,extraction filter,fixed point method,parallel factor decomposition,sequential separation scheme,higher order statistics,matrix decomposition,mimo,correlation,tensile stress,computer simulation,indexes
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要