scholarly journals IMPROVED BLIND SOURCE EXTRACTION FOR TIME DELAY ESTIMATE IN PASSIVE COHERENT LOCATION SYSTEM

2012 ◽  
Vol 37 ◽  
pp. 257-274 ◽  
Author(s):  
Ge Ge Zhang ◽  
Jun Wang ◽  
Hong Wei Li ◽  
Hui Huang
2013 ◽  
Vol 756-759 ◽  
pp. 3841-3844
Author(s):  
Yong Jian Zhao ◽  
Hai Ning Jiang ◽  
Mei Xia Qu

This paper proposes a blind source extraction (BSE) method on the basis of several time-delay autocorrelations from primary sources. This method is a second-order statistic learning algorithm, which can extract a desired biomedical signal while it shows a specific temporal structure. In contrast to conventional BSE methods, it is simple and do not need to choose any learning step size. Computer simulations on biomedical measurements demonstrate its validity and high performance in the process of revealing the underlying desired signal.


2014 ◽  
Vol 989-994 ◽  
pp. 3609-3612
Author(s):  
Yong Jian Zhao

Blind source extraction (BSE) is a promising technique to solve signal mixture problems while only one or a few source signals are desired. In biomedical applications, one often knows certain prior information about a desired source signal in advance. In this paper, we explore specific prior information as a constrained condition so as to develop a flexible BSE algorithm. One can extract a desired source signal while its normalized kurtosis range is known in advance. Computer simulations on biomedical signals confirm the validity of the proposed algorithm.


2013 ◽  
Vol 756-759 ◽  
pp. 3845-3848
Author(s):  
Yong Jian Zhao ◽  
Mei Xia Qu ◽  
Hai Ning Jiang

The famous FastICA algorithm has been widely used for blind signal separation. For every process, it only converges to an original source which has the maximum negentropy of the underlying signals. To ensure the first output is the desired signal, we incorporate a priori knowledge as a constraint into the FastICA algorithm to construct a robust blind source extraction algorithm. One can extract the desired signal if its normalized kurtosis is known to lie in a specific range, whereas other unwanted signals do not belong to this range. Experimental results on biomedical signals illustrate the validity and reliability of the proposed method.


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