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中文摘要：
两步法是解决稀疏信号欠定盲分离的一种常用方法，通常首先利用K-means聚类算法估计混叠矩阵，然后利用最短路径法恢复源信号。在使用K-means聚类算法时要求知道源信号的数目，而现实中往往不知道源信号的数目，需要对其进行估计。因此研究了聚类有效性评价指标——BWP指标，结合粒子群算法，提出了一种改进的确定源信号数目的算法，并将这种算法引入到欠定盲分离。实验表明，提出的算法在保证分离精度的同时能缩短分离时间，并可节省一定的内存，在观测信号数据量大时，这种优势更加明显。
英文摘要：
Two-step method is a commonly used solution to the underdetermined blind source separation of sparse source sig- nals, K-means clustering algorithm is usually utilized to estimate mixing matrix firstly, and then, the shortest path algorithm is used to recover source signals. The source signal＇ s number needed in the K-means clustering algorithm is usually unknown in fact, so have to estimate it. This paper studied clustering validity index ： BWP index, combined with particle swarm optimiza- tion, proposed a new algorithm to determine the source signal＇ s number. Then it introduced the proposed algorithm into the un- derdetermined blind source separation. The results of experiment show that the proposed algorithm has good separation preci- sion, meanwhile it can shorten the separation time and save some memory, this advantage is more obvious when the observation data is huge.
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