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INFORMATION THEORETIC FEATURE PROJECTION FOR SINGLE-TRIAL BRAIN-COMPUTER INTERFACES
Current approaches on optimal spatio-spectral feature extraction for single-trial BCIs exploit mutual information based feature ranking and selection algorithms. In order to overcome potential confounders underlying feature selection by information theoretic criteria, we propose a non-parametric fea...
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| 出版年: | IEEE Int Workshop Mach Learn Signal Process |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2017
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6525614/ https://ncbi.nlm.nih.gov/pubmed/31110907 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/MLSP.2017.8168178 |
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