A novel approach for underdetermined blind sources separation in frequency domain

作者：Xiao, Ming; Xie, Shengli; Fu, Yuli

来源：Second International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005 , Chongqing, 2005-05-30 To 2005-06-01.

DOI：10.1007/11427445_79

• Matrix recovery
• Short time fourier transforms

In this paper, we discussed the separation of n sources from m linear mixtures when the underlying system is underdetermined, that is, when m<n. The underdetermined blind sources separation has two steps. In matrix-recovery step, we defined a characteristic of the signals as the durative-sparsity and proposed a novel approach called as a searching-and-averaging-based method in frequency domain. This approach tells us how to search some data points that are very close to the basis lines along the direction of basis vectors a jand how to use them to estimate the mixing matrix. In source-recovery step, we used Bofill and Zibulevsky's shortest-path algorithm. Finally, the separation results were obtained using their short-time Fourier transforms.

• 出版日期2005
• 单位华南理工大学