摘要
提出了一种基于Gabor变换的盲信号分离方法。与传统的盲信号分离方法相比,该方法考虑到了不同类型信号的时频分布特点,通过估计混合矩阵从而能够较为准确地对源信号进行分离,而且突破了传统盲信号分离方法中要求源信号相互独立以及源信号最多只能有一个高斯信号的限制。仿真结果验证了该方法的有效性,为盲信号分离技术提供一种新的研究方向。
A new method of blind source separation(BSS)based on Gabor transformation was proposed.Compared with the traditional BSS methods,this new method could obtain the estimate of the mixing matrix so as to separate the mixing signals based on the characteristics of time-frequency distribution of the source signals.Even if the source signals were correlative,or there were more than one Gaussian signal in the sources,one could get better separation performance by using this new method.The simulation results showed the feasibility and validity of the method,it may provide a new research direction for blind signal separation.
出处
《振动与冲击》
EI
CSCD
北大核心
2010年第10期166-169,共4页
Journal of Vibration and Shock
基金
国家自然科学基金(10602038
50625518
10932006)
教育部科学技术研究重点项目(209013)资助课题
关键词
盲信号分离
GABOR变换
时频分布
信噪比
blind source separation(BSS)
Gabor transformation
time-frequency analysis
signal to noise ratio(SNR)