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Source Signals' Number Estimation Based on Fuzzy Clustering in Blind Separation of BPSK Signals

机译:基于模糊聚类的源信号'数量估计在BPSK信号的盲分离中

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Digital signals are used in modern communication, and it is very important to focus on it. Although there have existed a lot of algorithms of blind separation, algorithms for blind separation of digital signals or blind separation of finite characters set are still few. What's more, algorithms for estimating the number of source signals in the case don't appear. In this paper, it gives a novel algorithm for BPSK signals' blind separation. First, it can estimate the number of source signals according to the characteristics of sensor signals in no noise and noise circumstance respectively. Finally, the mixture matrix is estimated accurately by using the relations of sensor signals, which is a primary column transformation of the original mixture matrix. They can be corrected by introducing headers in the bit-streams and differently encoding them. The algorithms are shown simple and efficient in last simulations.
机译:数字信号用于现代通信,专注于它非常重要。虽然已经存在许多盲分离算法,但是用于盲目分离的数字信号或有限字符集的盲分离算法仍然很少。更重要的是,用于估计案例中源信号数量的算法不会出现。在本文中,它给出了一种用于BPSK信号“盲分离的新算法。首先,它可以分别在没有噪声和噪声环境中根据传感器信号的特性估计源信号的数量。最后,通过使用传感器信号的关系精确地估计混合物矩阵,这是原始混合矩阵的主要柱变换。它们可以通过引入位流中的标题并以不同的编码它们来校正。算法在最后一次模拟中显示简单且有效。

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