A signal-dependent quadratic time frequency distribution for neural source estimation

被引：0
|
作者：
Wang, Pu [1 ]
Yang, Jianyu
Zhang, Zhi-Lin
Wang, Gang
Mo, Quanyi
机构：
[1] Univ Elect Sci & Technol China, Sch Elect Engn, Chengdu 610054, Peoples R China
[2] Univ Elect Sci & Technol China, Blind Source Separat Res Grp, Chengdu 610054, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 2, PROCEEDINGS | 2006年 / 3972卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel method for kernel design of a quadratic time frequency distribution (TFD) as the initial step for neural source estimation is proposed. The kernel is constructed based on the product ambiguity function (AF), which efficiently suppresses cross terms and noise in the ambiguity domain. In order to reduce the influence from the strong signal to the weak signal, an iterative approach is implemented. Simulation results validate the method and demonstrate suppression of cross terms and noise, and high resolution in the time frequency domain.
引用
收藏
页码：700 / 705
页数：6
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