研究欠定盲源分离中的混合矩阵估计问题，针对多源时频点对混合矩阵估计的影响，提取时频域单源点用于混合矩阵估计，给出一种时频单源点检测方法. 针对时频单源点中孤立点对混合矩阵估计的影响，剔除单源点中的孤立点进一步提高混合矩阵的估计精度，应用减法聚类方法对剔除孤立点后的时频单源点进行聚类，实现了源信号数目和混合矩阵的同时估计. 语音信号的仿真实验表明，与其他两种基于时频单源点的欠定混合矩阵估计算法相比，所提出的算法具有更高的估计精度和更好的鲁棒性.

This paper focuses on the mixing matrix estimation in underdetermined blind source separation.A method for detecting the single source points in the time-frequency (TF) domain is given to reduce the effect of multiple source points in the TF domain. A method of outlier detection is used to remove outliers
in the single source points to improve accuracy of mixing matrix estimation. A subtractive clustering method is used to cluster the single source points so that the number of sources and the mixing matrix are obtained simultaneously. Experiments on speech signals show that the proposed algorithm can estimate the mixing matrix with high accuracy and robustness as compared to the other two mixing matrix estimation algorithms based on single source point detection in the TF domain.