一種線性混合信號(hào)盲提取算法
An Algorithm for Blind Signal Extraction of Linear Mixture
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摘要: 該文給出了信號(hào)變化度的定義，并證明了獨(dú)立源信號(hào)的線性混合信號(hào)(非零信號(hào))的變化度介于源信號(hào)中的最小變化度和最大變化度之間。在此性質(zhì)的基礎(chǔ)上，給出了一種線性混合信號(hào)盲提取算法。該算法首先利用廣義特征值理論從混合信號(hào)中提取出一個(gè)源信號(hào), 然后采用消源方法剔出混合信號(hào)中該源信號(hào)分量，重復(fù)這一過(guò)程，逐一提取出所有的源信號(hào)。該算法計(jì)算簡(jiǎn)單，仿真結(jié)果表明該算法是有效的，并具有很好的性能。
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關(guān)鍵詞:
- 信號(hào)變化度;盲信號(hào)提取;廣義特征值
Abstract: In this paper, a measure of signal variability is defined. Given any set of statistically independent source signals, it is proved here that a linear mixture of those signals has the following property: the signal variability of any signal mixture is greater than (or equal to) minimal that of its component source signals, and is less than (or equal to) maximal that of its component source signals. Based on the property, an algorithm for linear blind signal extraction is proposed. In the proposed algorithm, the source signal is extracted one by one by using generalized eigenvalue theory and deflation approach. The presented algorithm has less computations. Simulation results illustrate the efficiency and the good performance of the algorithm. -
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