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A semi-supervised support vector machine approach for parameter setting in motor imagery-based brain computer interfaces
Parameter setting plays an important role for improving the performance of a brain computer interface (BCI). Currently, parameters (e.g. channels and frequency band) are often manually selected. It is time-consuming and not easy to obtain an optimal combination of parameters for a BCI. In this paper...
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| 主要な著者: | , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer Netherlands
2010
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2918756/ https://ncbi.nlm.nih.gov/pubmed/21886673 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11571-010-9114-0 |
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