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Performance Evaluation of the Champagne Source Reconstruction Algorithm on Simulated and Real M/EEG Data
In this paper, we present an extensive performance evaluation of a novel source localization algorithm, Champagne. It is derived in an empirical Bayesian framework that yields sparse solutions to the inverse problem. It is robust to correlated sources and learn the statistics of non-stimulus-evoked...
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| Main Authors: | , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2011
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4096349/ https://ncbi.nlm.nih.gov/pubmed/22209808 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2011.12.027 |
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