1 April 2003 Progress in blind separation of magnetoencephalographic data
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Proceedings Volume 5102, Independent Component Analyses, Wavelets, and Neural Networks; (2003); doi: 10.1117/12.502478
Event: AeroSense 2003, 2003, Orlando, Florida, United States
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.
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Barak A. Pearlmutter, Santiago Jaramillo, "Progress in blind separation of magnetoencephalographic data", Proc. SPIE 5102, Independent Component Analyses, Wavelets, and Neural Networks, (1 April 2003); doi: 10.1117/12.502478; http://dx.doi.org/10.1117/12.502478
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