局部充分稀疏的欠定时盲信号源分离

Underdetermined Blind Source Separation Based on Locally Sparse Representations

针对欠定时的盲信号分离,提出了局部充分稀疏条件下估计混叠矩阵A的新算法.该算法不要求源信号所有采样时刻都充分稀疏,先通过搜索,把处于同一直线的向量一一归类,再对所得的类的向量进行处理,把混叠矩阵A确定出来.仿真实验结果表明算法是有效的.

It proposes a new algorithm of locally sparse blind source separation for estimating the mixed matrix A. This method doesn＇ t require all the samples of the sources are strictly sparse. Firstly all the vectors in the same line were searched for and classified. And then the mixed matrix A determined. The simulation illustrates the effectiveness of this algorithm.