Xiang Yong, Ng Sze Kui, Nguyen Van Khanh
School of Engineering, Deakin University, Geelong, Vic 3217, Australia.
IEEE Trans Neural Netw. 2010 Jan;21(1):82-90. doi: 10.1109/TNN.2009.2034518. Epub 2009 Nov 24.
This paper studies the problem of blind source separation (BSS) from instantaneous mixtures with the assumption that the source signals are mutually correlated. We propose a novel approach to BSS by using precoders in transmitters. We show that if the precoders are properly designed, some cross-correlation coefficients of the coded signals can be forced to be zero at certain time lags. Then, the unique correlation properties of the coded signals can be exploited in receiver to achieve source separation. Based on the proposed precoders, a subspace-based algorithm is derived for the blind separation of mutually correlated sources. The effectiveness of the algorithm is illustrated by simulation examples.
本文研究在源信号相互关联的假设下，从瞬时混合信号中进行盲源分离（BSS）的问题。我们提出一种通过在发射机中使用预编码器来实现BSS的新方法。我们表明，如果预编码器设计得当，编码信号的一些互相关系数在特定时间滞后可以被强制为零。然后，在接收机中可以利用编码信号独特的相关特性来实现源分离。基于所提出的预编码器，推导了一种用于相互关联源的盲分离的基于子空间的算法。通过仿真示例说明了该算法的有效性。
