首页> 外文会议>Fuzzy Systems and Knowledge Discovery,(FSKD), 2008 Fifth International Conference on >Source Signals' Number Estimation Based on Fuzzy Clustering in Blind Separation of BPSK Signals
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Source Signals' Number Estimation Based on Fuzzy Clustering in Blind Separation of BPSK Signals

机译:BPSK信号盲分离中基于模糊聚类的源信号数估计

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摘要

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:数字信号被用于现代通信中,因此专注于数字信号非常重要。尽管存在许多盲分离算法,但是用于数字信号的盲分离或有限字符集的盲分离的算法仍然很少。而且,在这种情况下,用于估计源信号数量的算法没有出现。本文提出了一种新的BPSK信号盲分离算法。首先,它可以根据无噪声和无噪声情况下传感器信号的特性分别估算源信号的数量。最后,通过利用传感器信号的关系准确地估计混合矩阵,这是原始混合矩阵的主要列变换。可以通过在比特流中引入标头并对它们进行不同的编码来纠正它们。在最后的仿真中,算法显示简单而有效。

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