An analysis of the CCA approach for blind source separation and its adaptive realization

Author

Liu, Wei ; Mandic, Danilo P. ; Cichocki, Andrzej

Author_Institution

Dept. of Electron. & Electr. Eng., Sheffield Univ.

fYear

2006

fDate

21-24 May 2006

Abstract

An analysis of the canonical correlation analysis (CCA) approach in blind source separation is provided. In particular, it is proved that by maximizing the autocorrelation functions of the recovered signals we can separate the source signals successfully. We show that the CCA approach represents the same generalised eigenvalue decomposition problem introduced in the matrix pencil method. Finally, an adaptive blind source extraction (BSE) algorithm is derived as an online realisation of the CCA approach. Simulation results verify the proposed approach

Keywords

blind source separation; correlation methods; eigenvalues and eigenfunctions; matrix decomposition; statistical analysis; adaptive blind source extraction; autocorrelation functions; blind source separation; canonical correlation analysis; eigenvalue decomposition problem; matrix pencil method; online realisation; Adaptive signal processing; Autocorrelation; Blind source separation; Covariance matrix; Educational institutions; Laboratories; Matrix decomposition; Signal processing algorithms; Source separation; Statistical distributions;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2006. ISCAS 2006. Proceedings. 2006 IEEE International Symposium on

Conference_Location

Island of Kos

Print_ISBN

0-7803-9389-9

Type

conf

DOI

10.1109/ISCAS.2006.1693403

Filename

1693403