A Time-Frequency Algorithm for Noisy BSS Model

摘要：

In most practical blind source separation (BSS) applications, the observations contain additive source noise that limits the performances of most existing BSS algorithms. In this paper, we propose a new BSS approach exploiting the difference in the time-frequency (t-f) signatures of these sources to be separated. The approach uses smooth pseudo WignerVille distribution (SPWVD) to obtain t-f distribution, then localizes the signal energy by Hough transform and selects a set of spatial t-f points based on the dominant eigenvalue of SPWVD of observations. Finally, numerical performance simulations are provided highlighting its effectiveness.

关键词： source noise Hough transform smooth pseudo Wigner-Ville distribution blind source separation

作者: Jing Guo Xiao-Ping Zeng

作者单位: School of Electronics and Information Engineering Southwest University Chongqing, P.R. China College College of Communication Engineering Chongqing University Chongqing, P.R. China

会议类型: 国际会议

会议名称: 2010 International Conference on Signal and Information Processing(2010年IEEE信号与信息处理国际会议 ICSIP2010)

会议地点: 长沙

会议语种:英文

页码: 42-46

在线出版日期: 2010-12-14（万方平台首次上网日期，不代表论文的发表时间）