中文摘要：

为了减少传统的截断混合矩阵求逆（ITMM）算法在个别时频点会丢失数据或者产生噪声信号的概率,提出了一种基于频域的2步欠定瞬时盲分离算法.由于现实中存在大量软稀疏（稀疏度不是很大）混合信号,将分离过程分解为ITMM和矩阵补偿2个步骤.首先估计出混合矩阵和利用经典的ITMM算法对混合信号进行初步恢复,然后对初步估计的信号时频矩阵进行矩阵补偿处理,从而达到修补丢失数据和去除多余数据（去噪）的效果.实验仿真验证了所提出的2步分离法相对于传统的ITMM算法能够得到更好的分离效果.此外,对算法的时耗问题进行了研究,相对于传统的ITMM算法,所提算法的时耗增加不到四分之一,却能够得到更好的分离效果.

英文摘要：

In order to decrease the probability of missing some data points or noises being added in the inverse truncated mixing matrix （ITMM） algorithm, a two-stage frequency- domain method is proposed for blind source separation of underdetermined instantaneous mixtures. The separation process is decomposed into two steps of ITMM and matrix completion in the view that there are many soft-sparse （not very sparse） sources. First, the mixing matrix is estimated and the sources are recovered by the traditional ITMM algorithm in the frequency domain. Then, in order to retrieve the missing data and remove noises, the matrix completion technique is applied to each preliminary estimated source by the traditional ITMM algorithm in the frequency domain. Simulations show that, compared with the traditional ITMM algorithms, the proposed two-stage algorithm has better separation performances. In addition, the time consumption problem is considered. The proposed algorithm outperforms the traditional ITMM algorithm at a cost of no more than one- fourth extra time consumption.