Independent component analysis algorithm and its application in biomedical engineering
10.3760/cma.j.issn.1673-4181.2011.04.014
- VernacularTitle:独立分量分析算法及在生物医学工程中的应用
- Author:
Xiaojuan MA
;
Ling ZOU
- Publication Type:Journal Article
- Keywords:
Second-order statistics;
Higher-order statistics;
Independent component analysis;
Biomedical signal;
Joint approximative aiagonalization of eigenmatrix
- From:
International Journal of Biomedical Engineering
2011;34(4):249-252,插3
- CountryChina
- Language:Chinese
-
Abstract:
Independent component algorithm (ICA) is a method of higher-order statistics(HOS) with the study objects of multivariate random signals that are mutual independent. It aim is to transform multivariate random signal into the signal having components that are mutually independent in complete statistical sense. This article briefly introduce series of the ICA algorisms including second order blind identification, multiple unknown source extraction algorithm based on second-order statistics, as well as Informax, modified Informax, fast fixedpoint ICA and joint approximative diagonalization of eigenmatrix (JADE) algorithm that are based on HOS. At the end of the article, the performance of each algorithm is compared and its application prospect is forecasted.
