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pubmed-article:20172787pubmed:abstractTextThis paper proposes a novel spatial filter for biomagnetic source imaging. The proposed spatial filter is derived based on a modified version of the minimum-norm spatial filter and is designed to have a performance close to that of the adaptive minimum-variance spatial filter through the use of an estimated covariance matrix. In this method, the theoretical form of the measurement covariance matrix is estimated as an updated gram matrix in a recursive procedure. Since the proposed method does not use the sample covariance matrix, it is free of the well-known weaknesses of the minimum-variance spatial filter, namely, the proposed spatial filter does not require a large number of time samples, and it can even be applied to single-time-sample data. It is also robust to source correlation. We have validated the method's effectiveness by our computer simulations as well as through experiments using auditory-evoked magnetoencephalographic data.lld:pubmed
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pubmed-article:20172787pubmed:authorpubmed-author:SekiharaKensu...lld:pubmed
pubmed-article:20172787pubmed:authorpubmed-author:KumihashiIsam...lld:pubmed
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pubmed-article:20172787pubmed:volume57lld:pubmed
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pubmed-article:20172787pubmed:year2010lld:pubmed
pubmed-article:20172787pubmed:articleTitleArray-gain constraint minimum-norm spatial filter with recursively updated gram matrix for biomagnetic source imaging.lld:pubmed
pubmed-article:20172787pubmed:affiliationDepartment of Systems Design and Engineering, Tokyo Metropolitan University, Tokyo 191-0065, Japan. kumihashi136_ac@yahoo.co.jplld:pubmed
pubmed-article:20172787pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:20172787pubmed:publicationTypeResearch Support, Non-U.S. Gov'tlld:pubmed
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