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Underdetermined Blind Separation Via Rough Equivalence Clustering for Satellite Communications

机译:通过粗糙的等价聚类进行卫星通信的粗略等效聚类而被确定的盲分离

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The problem of underdetermined blind source separation for satellite communications is proposed in this paper. In underdetermined blind separation, people suppose the source is sparse and the number of source signals is known when they estimate the mixture matrix. In fact, the sparsity is often not satisfied and the number of source signals is unknown. This paper presents a novel Rough Set algorithm (RS algorithm) based on rough set theory, which can get the source signal sparse points and accurately estimate the number of sources and the mixture matrix respectively, by which source signals can be reconstructed. The last simulations show the good performance of the paper's algorithm.
机译:本文提出了卫星通信的未确定盲源分离的问题。在未确定的盲分离中,人们假设源是稀疏的,并且当它们估计混合矩阵时,源信号的数量是已知的。实际上,少于不满足的稀疏性,并且源信号的数量未知。本文介绍了一种基于粗糙集理论的新型粗糙集算法(RS算法),其可以获得源信号稀疏点,并分别精确估计源极和混合矩阵的数量,通过该源信号可以重建源信号。最后一次模拟显示了纸张算法的良好表现。

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