摘要
提出了一种新的频域盲分离排序算法。算法对不同频率点采用不同的排序算法:频率较低部分采用比较分离信号相邻频率点和谐波频率点之间幅度相关性相结合的排序算法;中频部分采用基于语音信号方位估计的排序算法;频率较高部分采用相关比较和方位估计结合的排序方法。仿真结果表明,该排序算法的鲁棒性和精确性较现有的单纯利用分离信号相关性的排序算法或者基于语音信号定位的排序算法有了一定的增强。
A new method for solving the permutationproblem in the frequency-domain Blind Source Separation （BSS） was presented. This new method divided the whole frequency-domain into three sections and applied different permutation algorithms to different sections. The neighboring frequency correlation and harmonic frequency correlation coefficient of signal amplitudes were used together for the low-frequency section, the direction of arrival estimation for speech sources for the mid- frequency section, and the combination of correlation coefficient comparison and direction estimation for the high-frequency sectibn, respectively. Experimental results show that the new method provides a more robust and precise solution to the permutation problem than the algorithm only with interfrequency correlation coefficient of signal amplitudes or only with direction of arrival estimation for sources.
出处
《计算机应用》
CSCD
北大核心
2008年第6期1552-1554,1562,共4页
journal of Computer Applications
基金
温州市科学技局资助项目(G20060102)
关键词
盲源分离
排序模糊性
方位估计
blind source separation
permutation ambiguity
direction of arrival estimation
