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Brain signal source localization from E/MEG has been an active research area. Currently, there exists var- ious approaches such as MUSIC and M-SBL. However, when the unknown sources are highly correlated, conventional algorithms often exhibit spurious reconstructions. To address the problem, we propose a new algorithm that generalizes M-SBL by exploiting the fundamental subspace geometry in the multiple...
Localization of brain signal sources from EEG/MEG has been an active area of research [1]. Currently, there exists a variety of approaches such as MUSIC [2], M-SBL [3], and etc. These algorithms have been applied for various clinical examples and demonstrated excellent performances. However, when the unknown sources are highly correlated, the conventional algorithms often exhibit spurious reconstructions...
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