Blind source separation using time-delayed signals

Author

Tomé, A.M. ; Teixeira, Ana R. ; Lang, E.W. ; Stadlthanner, K. ; Rocha, A.P. ; Almeida, R.

Author_Institution

Univ. de Aveiro, Aveiro, Portugal

Volume

3

fYear

2004

fDate

25-29 July 2004

Firstpage

2187

Abstract

In this work a modified version of AMUSE, called dAMUSE, is proposed. The main modification consists in increasing the dimension of the data vectors by joining delayed versions of the observed mixed signals. With the new data a matrix pencil is computed and its generalized eigendecomposition is performed as in AMUSE. We will show that in this case the output (or independent) signals are filtered versions of the source signals. Some numerical simulations using artificially mixed signals as well as biological data (RR and QT intervals of Electrocardiogram) are presented.

Keywords

blind source separation; eigenvalues and eigenfunctions; matrix decomposition; numerical analysis; artificially mixed signals; biological data; blind source separation; data vectors; eigen decomposition; matrix decomposition; numerical simulations; observed mixed signals; time delayed signals; Blind source separation; Delay; Eigenvalues and eigenfunctions; Frequency estimation; Heart rate interval; Higher order statistics; Independent component analysis; Matrix decomposition; Signal processing; Source separation;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on

ISSN

1098-7576

Print_ISBN

0-7803-8359-1

Type

conf

DOI

10.1109/IJCNN.2004.1380958

Filename

1380958