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一种线性混合信号盲提取算法
引用本文:高鹰, 谢胜利. 一种线性混合信号盲提取算法[J]. 电子与信息学报, 2006, 28(6): 999-1003.
作者姓名:高鹰  谢胜利
作者单位:广州大学计算机科学与技术系,广州,510405;华南理工大学电子与信息学院,广州,510641;华南理工大学电子与信息学院,广州,510641
基金项目:国家杰出青年科学基金;国家自然科学基金;广东省自然科学基金;教育部跨世纪优秀人才培养计划;中国博士后科学基金;广东省教育厅自然科学基金;广东省广州市科技计划;广东省广州市属高校科技计划
摘    要:该文给出了信号变化度的定义,并证明了独立源信号的线性混合信号(非零信号)的变化度介于源信号中的最小变化度和最大变化度之间。在此性质的基础上,给出了一种线性混合信号盲提取算法。该算法首先利用广义特征值理论从混合信号中提取出一个源信号, 然后采用消源方法剔出混合信号中该源信号分量,重复这一过程,逐一提取出所有的源信号。该算法计算简单,仿真结果表明该算法是有效的,并具有很好的性能。

关 键 词:信号变化度  盲信号提取  广义特征值
文章编号:1009-5896(2006)06-0999-05
收稿时间:2004-10-25
修稿时间:2005-04-07

An Algorithm for Blind Signal Extraction of Linear Mixture
Gao Ying, Xie Sheng-li. An Algorithm for Blind Signal Extraction of Linear Mixture[J]. Journal of Electronics & Information Technology, 2006, 28(6): 999-1003.
Authors:Gao Ying  Xie Sheng-li
Affiliation:Dept. of Computer Science and Technology., Guangzhou University, Guangzhou 510405, China;College of Electronic & Information Engineering, South China University of Technology, Guangzhou 510641, China
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.
Keywords:Signal variability   Blind signal extraction   Generalized eigenvalue
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