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Independent component analysis algorithm and its application in biomedical engineering / 国际生物医学工程杂志
International Journal of Biomedical Engineering ; (6): 249-252,插3, 2011.
Article Dans Chinois | WPRIM | ID: wpr-597974
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.

Texte intégral: Disponible Indice: WPRIM (Pacifique occidental) Type d'étude: Étude pronostique langue: Chinois Texte intégral: International Journal of Biomedical Engineering Année: 2011 Type: Article

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Texte intégral: Disponible Indice: WPRIM (Pacifique occidental) Type d'étude: Étude pronostique langue: Chinois Texte intégral: International Journal of Biomedical Engineering Année: 2011 Type: Article