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Complex independent component analysis of frequency-domain electroencephalographic data
Independent component analysis (ICA) has proven useful for modeling brain and electroencephalographic (EEG) data. Here, we present a new, generalized method to better capture the dynamics of brain signals than previous ICA algorithms. We regard EEG sources as eliciting spatio-temporal activity patte...
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| Hoofdauteurs: | , , |
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| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
2003
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2925861/ https://ncbi.nlm.nih.gov/pubmed/14622887 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neunet.2003.08.003 |
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