期刊
SCIENCE IN CHINA SERIES F-INFORMATION SCIENCES
卷 49, 期 5, 页码 639-652出版社
SCIENCE PRESS
DOI: 10.1007/s11432-006-2020-8
关键词
ill-posed mixture; blind source separation; sparse representation; PCA; K-mean clustering
Bofill et al. discussed blind source separation (BSS) of sparse signals in the case of two sensors. However, as Bofill et al. pointed out, this method has some limitation. The potential function they introduced is lack of theoretical basis. Also the method could not be extended to solve the problem in the case of more than three sensors. In this paper, instead of the potential function method, a K-PCA method (combining K-clustering with PCA) is proposed. The new method is easy to be used in the case of more than three sensors. It is easy to be implemented and can provide accurate estimation of mixing matrix. Some criterion is given to check the effect of the mixing matrix A. Some simulations illustrate the availability and accuracy of the method we proposed.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据