Blind separation for mixtures of sub-Gaussian and super-Gaussian sources

Author

Ihm, B.C. ; Ark, D. J P ; Kwon, K.H.

Author_Institution

Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea

Volume

3

fYear

2000

fDate

2000

Firstpage

738

Abstract

We propose a new intelligent blind source separation algorithm for the mixture of sub-Gaussian and super-Gaussian sources. The algorithm consists of an update equation of the separating matrix and an adjustment equation of nonlinear functions. The weighted sum of two nonlinear functions is adapted to obtain the proper nonlinear function for each source. To verify the validity of the proposed algorithm, we compare the result with that of algorithms with one fixed nonlinear function, and that of the extant methods

Keywords

array signal processing; higher order statistics; nonlinear functions; signal detection; adjustment equation; blind separation; nonlinear functions; separating matrix; source separation algorithm; sub-Gaussian sources; super-Gaussian sources; update equation; weighted sum; Biomedical measurements; Blind source separation; Ear; Feature extraction; Image processing; Mutual information; Nonlinear equations; Probability density function; Source separation; Speech recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on

Conference_Location

Geneva

Print_ISBN

0-7803-5482-6

Type

conf

DOI

10.1109/ISCAS.2000.856166

Filename

856166