NDLI: An efficient semi-blind source extraction algorithm and its applications to biomedical signal extraction

Content Provider	Springer Nature Link
Author	Ye, YaLan Sheu, Phillip C. Y. Zeng, JiaZhi Wang, Gang Lu, Ke
Copyright Year	2009
Abstract	In many applications, such as biomedical engineering, it is often required to extract a desired signal instead of all source signals. This can be achieved by blind source extraction (BSE) or semi-blind source extraction, which is a powerful technique emerging from the neural network field. In this paper, we propose an efficient semi-blind source extraction algorithm to extract a desired source signal as its first output signal by using a priori information about its kurtosis range. The algorithm is robust to outliers and spiky noise because of adopting a classical robust contrast function. And it is also robust to the estimation errors of the kurtosis range of the desired signal providing the estimation errors are not large. The algorithm has good extraction performance, even in some poor situations when the kurtosis values of some source signals are very close to each other. Its convergence stability and robustness are theoretically analyzed. Simulations and experiments on artificial generated data and real-world data have confirmed these results.
Starting Page	1863
Ending Page	1874
Page Count	12
File Format	PDF
ISSN	10092757
Journal	Science in China Series : Information Sciences
Volume Number	52
Issue Number	10
e-ISSN	18622836
Language	English
Publisher	SP Science in China Press
Publisher Date	2009-10-06
Publisher Place	Heidelberg
Access Restriction	Subscribed
Subject Keyword	blind source extraction blind source separation independent component analysis electrocardiogram fetal ECG Atrial Fibrillation Information Systems and Communication Service
Content Type	Text
Resource Type	Article
Subject	Computer Science

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