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IJON
2002

Extraction of a source from multichannel data using sparse decomposition

9 years 6 months ago
Extraction of a source from multichannel data using sparse decomposition
It was discovered recently that sparse decomposition by signal dictionaries results in dramatic improvement of the qualities of blind source separation. We exploit sparse decomposition of a source in order to extract it from multidimensional sensor data, in applications where a rough template of the source is known. This leads to a convex optimization problem, which is solved by a Newton-type method. Complete and overcomplete dictionaries are considered. Simulations with synthetic evoked responses mixed into natural 122-channel MEG data show signi
Michael Zibulevsky, Yehoshua Y. Zeevi
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 2002
Where IJON
Authors Michael Zibulevsky, Yehoshua Y. Zeevi
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