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

作　　者：YE YaLan SHEU Phillip C-Y ZENG JiaZhi WANG Gang LUKe 

机构地区：[1]School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China [2]Department of Electrical Engineering and Computer Science, University of California, Irvine, CA 92697-2625, USA [3]School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China

出　　处：《Science in China(Series F)》2009年第10期1863-1874,共12页中国科学（F辑英文版）

基　　金：Supported by the National Natural Science Foundation of China (Grant No. 60702072), and China Scholarship Council

摘　　要：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.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.

关 键 词：blind source extraction blind source separation independent component analysis ELECTROCARDIOGRAM fetal ECG Atrial Fibrillation 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] TB383[自动化与计算机技术—计算机科学与技术]