Blind source extraction using spatio-temporal inverse filter

2009 ◽  
Author(s):  
Yoshikazu Washizawa ◽  
Yukihiko Yamashita ◽  
Andrzej Cichocki
Keyword(s):  
Inverse Filter ◽  
Blind Source Extraction ◽  
Spatio Temporal ◽  
Source Extraction

Research on Blind Signal Extraction Based on Normalized Kurtosis

2014 ◽  
Vol 989-994 ◽  
pp. 3609-3612
Author(s):  
Yong Jian Zhao
Keyword(s):  
Biomedical Applications ◽  
Prior Information ◽  
Signal Extraction ◽  
Promising Technique ◽  
Blind Source Extraction ◽  
Blind Signal ◽  
Source Signal ◽  
Blind Signal Extraction ◽  
Source Signals ◽  
Source Extraction

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.

A Method for Extracting Signals with Specific Normalized Kurtosis Range

2013 ◽  
Vol 756-759 ◽  
pp. 3845-3848
Author(s):  
Yong Jian Zhao ◽  
Mei Xia Qu ◽  
Hai Ning Jiang
Keyword(s):  
A Priori ◽  
Signal Separation ◽  
Blind Signal Separation ◽  
Validity And Reliability ◽  
Original Source ◽  
Blind Source Extraction ◽  
Blind Signal ◽  
Extraction Algorithm ◽  
Fastica Algorithm ◽  
Source Extraction

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.

Comparison between time reversal and spatio‐temporal inverse filter application to focusing through a human skull

2001 ◽  
Vol 109 (5) ◽  
pp. 2397-2397
Author(s):  
Mickael Tanter ◽  
Jean‐Francois Aubry ◽  
Jean‐Louis Thomas ◽  
Mathias Fink
Keyword(s):  
Time Reversal ◽  
Inverse Filter ◽  
Human Skull ◽  
Spatio Temporal
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