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dc.contributor.authorAdler, Amir
dc.contributor.authorWax, Mati
dc.contributor.authorPantazis, Dimitrios
dc.date.accessioned2019-09-03T17:26:45Z
dc.date.available2019-09-03T17:26:45Z
dc.date.issued2019-08-29
dc.identifier.urihttps://hdl.handle.net/1721.1/122034
dc.description.abstractWe present a novel solution to the problem of localization of brain signals. The solution is sequential and iterative, and is based on minimizing the least-squares (LS) criterion by the alternating projection (AP) algorithm, well known in the context of array signal processing. Unlike existing solutions belonging to the linearly constrained minimum variance (LCMV) and to the multiple-signal classification (MUSIC) families, the algorithm is applicable even in the case of a single sample and in the case of synchronous sources. The performance of the solution is demonstrated via simulations.en_US
dc.description.sponsorshipThis work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216.en_US
dc.publisherCenter for Brains, Minds and Machines (CBMM), arXiven_US
dc.relation.ispartofseriesCBMM Memo;099
dc.titleBrain Signals Localization by Alternating Projectionsen_US
dc.typeTechnical Reporten_US
dc.typeWorking Paperen_US
dc.typeOtheren_US


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