Improved blind source separation method based on independent component analysis and empirical mode decomposition

Author

Jie, Zhang ; Jianhui, Lin

Author_Institution

Sch. of Mech. Eng., Southwest Jiaotong Univ., Chengdu, China

Volume

4

fYear

2011

fDate

15-17 Oct. 2011

Firstpage

2217

Lastpage

2219

Abstract

Blind source separation (BSS) has recently received a great deal of attention in signal processing. In order to improve the limited separation performance of the conventional BSS method by the influence of the probability density of the source signal, based on the Independent Component Analysis and Empirical Mode Decomposition theories, an improved blind separation method is proposed. The method is demonstrated by some examples. Simulation results show the improved separation performance of the proposed method, and the time-frequency feature of the source signal has a better reflection.

Keywords

blind source separation; independent component analysis; medical signal processing; probability; time-frequency analysis; blind source separation; empirical mode decomposition; independent component analysis; probability density; signal processing; source signal; time-frequency feature; Algorithm design and analysis; Blind source separation; Educational institutions; Independent component analysis; Sensors; Signal processing algorithms; blind source separation; empirical mode decomposition; independent component analysis; non-stationary processes; probability density;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-9351-7

Type

conf

DOI

10.1109/BMEI.2011.6098718

Filename

6098718