A New Implement Method for Mazimizing Autocorrelation in Blind Signal Separation
Separating signal sources by maximizing the autocorrelation (also called the time delay correlation) of the interesting signal is a group of important blind source separation methods (BSS). Relying on the fact that the interesting practical sources vary more smoothly than noise, they made inspiring success in analysis of brain mapping data. However, by well investigating these algorithms, we find that they made an unnoticed assumption in maximizing the autocor relation of signal source. Unfortunately, this assump tion, which believes that the time delayed covariance matrix is symmetrical, is not well met in general. In the present study, a new method to maximize autocorrela tion is proposed. It does not rely on such assumption, and shows a better performance than traditional algorithm in the compare experiment. It is also proved that, the traditional algorithms and our method are equal to each other if the assumption is met.
Ming Li Yadong Liu Dewen Hu
College of Mechatronics and Automation,National University of Defense Technology,Changsha 410073,Hunan,China
国际会议
长沙
英文
403-406
2009-04-11（万方平台首次上网日期，不代表论文的发表时间）