FREQUENCY OVERLAPPED SIGNAL IDENTIFICATION USING BLIND SOURCE SEPARATION  

作　　者：WANG Junfeng SHI Tielin HE Lingsong YANG Shuzi 

机构地区：[1]College of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074, China [2]Wuhan National Laboratory for Optoelectronics,Wuhan 430074, China

出　　处：《Chinese Journal of Mechanical Engineering》2006年第2期286-289,共4页中国机械工程学报（英文版）

基　　金：This project is supported by National Natural Science Foundation of China(No.50405033).

摘　　要：The concepts, principles and usages of principal component analysis （PCA） and independent component analysis （ICA） are interpreted. Then the algorithm and methodology of ICA-based blind source separation （BSS）, in which the pre-whitened based on PCA for observed signals is used, are researched. Aiming at the mixture signals, whose frequency components are overlapped by each other, a simulation of BSS to separate this type of mixture signals by using theory and approach of BSS has been done. The result shows that the BSS has some advantages what the traditional methodology of frequency analysis has not.The concepts, principles and usages of principal component analysis （PCA） and independent component analysis （ICA） are interpreted. Then the algorithm and methodology of ICA-based blind source separation （BSS）, in which the pre-whitened based on PCA for observed signals is used, are researched. Aiming at the mixture signals, whose frequency components are overlapped by each other, a simulation of BSS to separate this type of mixture signals by using theory and approach of BSS has been done. The result shows that the BSS has some advantages what the traditional methodology of frequency analysis has not.

关 键 词：Principal component analysis（PCA） Independent component analysis（ICA） Blind source separation （BSS） 

分 类 号：TN911[电子电信—通信与信息系统]