A new method for blind source separation

Author

Nie, Ling-ye ; Li, Clei ; Chen, Cjia-ming

Author_Institution

Inst. of Autom. Control Eng. of NanJing, Univ. of Posts & Telecommun., Nanjing

Volume

4

fYear

2008

fDate

12-15 July 2008

Firstpage

2217

Lastpage

2222

Abstract

A method of network component analysis(NCA) which separates blind sources using a priori information on the mixing matrix was put forward. Therefore blind source separation can be achieved without the assumption of statistical independence. Performance analysis is given comparing to FastICA and JADE through computer simulation. The superiority of NCA is validated without the assumption of statistical independence.

Keywords

blind source separation; independent component analysis; matrix algebra; FastICA; JADE; blind source separation; computer simulation; mixing matrix; network component analysis; performance analysis; statistical independence; Biomedical signal processing; Blind source separation; Higher order statistics; Independent component analysis; Machine learning; Pattern analysis; Signal analysis; Signal processing; Signal processing algorithms; Vectors; Blind Source Separation(BSS); Independent Component Analysis(ICA); Network Component Analysis(NCA);

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2008 International Conference on

Conference_Location

Kunming

Print_ISBN

978-1-4244-2095-7

Electronic_ISBN

978-1-4244-2096-4

Type

conf

DOI

10.1109/ICMLC.2008.4620774

Filename

4620774