摘要
针对盲信号分离需要判断分离结果与源信号是否一致的问题,基于统计独立变量函数仍然保持“统计独立”的性质,提出了独立分量分析(ICA)的输出分量与源信号的一致性判断方法.该方法通过计算混合信号及其差分值混合矩阵的相关矩阵,根据ICA各分量对应的最大相关系数来判断ICA各分量与源信号的一致性.模拟计算和实验结果表明:若差分前后混合矩阵的最大相关系数趋近于1,则ICA输出分量与对应的源信号一致;为保证分离的准确,差分前后混合矩阵的最大相关系数不应小于0.8.
In the blind source separation (BSS), it is necessary to judge whether the BSS outputs are consistent with the source signals. In this paper, based on the statistical independence of statistical independence variable functions, a method to judge the consistency of the outputs in independent component analysis (ICA) with the source signals is presented. In this method, the correlation matrix of two mixing matrices which respectively belong to the source signals and the source differences is calculated, and the consistencies of the independent components with the source signals are then judged according to the maximum correlation coeflqcients corresponding to each independent component. Simulated and experimental results indicate that the independent components are consistent with the corresponding source signals when the maximum correlation coefficients converge and that the maximum correlation coeflqcient should not be less than 0. 8 to ensure the separation accuracy.
出处
《华南理工大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2007年第5期50-53,共4页
Journal of South China University of Technology(Natural Science Edition)
基金
中国博士后科学基金资助项目(2005037583)
广西自然科学基金资助项目(桂科基0448010)
关键词
盲信号分离
独立分量分析
差分
可靠性
Blind Source Separation
Independent Component Analysis
difference
reliability