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Proceedings Paper

Progress in blind separation of magnetoencephalographic data
Author(s): Barak A. Pearlmutter; Santiago Jaramillo
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Paper Abstract

The match between the physics of MEG and the assumptions of the most well developed blind source separation (BSS) algorithms (unknown instantaneous linear mixing process, many sensors compared to expected recoverable sources, large data limit) have tempted researchers to apply these algorithms to MEG data. We review some of these efforts, with particular emphasis on our own work.

Paper Details

Date Published: 1 April 2003
PDF: 6 pages
Proc. SPIE 5102, Independent Component Analyses, Wavelets, and Neural Networks, (1 April 2003); doi: 10.1117/12.502478
Show Author Affiliations
Barak A. Pearlmutter, National Univ. of Ireland, Maynooth (Ireland)
Santiago Jaramillo, National Univ. of Ireland, Maynooth (Ireland)

Published in SPIE Proceedings Vol. 5102:
Independent Component Analyses, Wavelets, and Neural Networks
Anthony J. Bell; Mladen V. Wickerhauser; Harold H. Szu, Editor(s)

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