A symmetric orthogonal FastICA algorithm and applications in EEG

doi:10.1109/ICNC.2009.482

	A symmetric orthogonal FastICA algorithm and applications in EEG
	Chen, Xuhui; Wang, Lei; Xu, Yong
	2009
会议日期	August 14, 2009 - August 16, 2009
会议地点	Tianjian, China
关键词	Estimation errors Fast convergence FastICA algorithms Independent components Matrix methods Orthogonal method Orthogonalization Separation efficiency
卷号	2
DOI	10.1109/ICNC.2009.482
页码	504-508
英文摘要	Extracting a number of independent components, FastICA algorithm can ensure that, each component extracted has never been extracted by adding orthogonalization steps. However, Gram-Schmidt orthogonal method implemented itself that estimation error of the first vector has been accumulated in the subsequent vectors. In this paper, the square root of the classical matrix method is used to achieve symmetric orthogonal that parallel to estimate the source of variables and avoid the Gram-Schmidt orthogonal method of estimation error accumulation problem. The symmetric orthogonal FastICA algorithm is apply in removal EEG artifacts (including eye movement, blinking, ECG, EMG, etc). The experiment and simulation results demonstrate that the symmetry orthogonal FastICA algorithm removes the artifacts and has a better separation efficiency and fast convergence. © 2009 IEEE.
会议录	5th International Conference on Natural Computation, ICNC 2009
会议录出版者	IEEE Computer Society
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/116368]
专题	实验室建设与管理处
作者单位	School of Computer Science and Communication, Lanzhou University of Technology, Lanzhou 730050, China
推荐引用方式 GB/T 7714	Chen, Xuhui,Wang, Lei,Xu, Yong. A symmetric orthogonal FastICA algorithm and applications in EEG[C]. 见:. Tianjian, China. August 14, 2009 - August 16, 2009.