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Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework
Methods for electro- or magnetoencephalography (EEG/MEG) based brain source imaging (BSI) using sparse Bayesian learning (SBL) have been demonstrated to achieve excellent performance in situations with low numbers of distinct active sources, such as event-related designs. This paper extends the theo...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433122/ https://www.ncbi.nlm.nih.gov/pubmed/34182100 http://dx.doi.org/10.1016/j.neuroimage.2021.118309 |