A Flexible Fully-Multiplicative Orthogonal-Group Based ICA Algorithm

Author

Ye, Yalan ; Wan, Jing ; Zhang, Zhi-Lin ; Jia, Chen ; Lei, Wu

Author_Institution

Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu

fYear

2007

fDate

1-5 April 2007

Firstpage

476

Lastpage

479

Abstract

In this paper, we propose a flexible fully-multiplicative orthogonal-group based ICA (FlexibleOgICA) algorithm, which can instantaneously separate the mixture of sub-Gaussian and super-Gaussian source signals. It adopts a self-adaptive nonlinear function, which adjusts its parameter to achieve better performance based on the estimation of the kurtosis of super-Gaussian source signals. We also have successfully applied the algorithm to obtain the fetal electrocardiogram (FECG) signal, showing its fast convergence speed and high separation performance

Keywords

Gaussian processes; independent component analysis; medical signal processing; FlexibleOgICA algorithm; fetal electrocardiogram signal; flexible fully-multiplicative orthogonal-group based ICA algorithm; self-adaptive nonlinear function; subGaussian source signal; superGaussian source signal; Bioinformatics; Biomedical signal processing; Computational biology; Computational intelligence; Convergence; Independent component analysis; Multidimensional signal processing; Signal processing; Signal processing algorithms; Switches;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Bioinformatics and Computational Biology, 2007. CIBCB '07. IEEE Symposium on

Conference_Location

Honolulu, HI

Print_ISBN

1-4244-0710-9

Type

conf

DOI

10.1109/CIBCB.2007.4221258

Filename

4221258