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An Incremental Version of L-MVU for the Feature Extraction of MI-EEG
Due to the nonlinear and high-dimensional characteristics of motor imagery electroencephalography (MI-EEG), it can be challenging to get high online accuracy. As a nonlinear dimension reduction method, landmark maximum variance unfolding (L-MVU) can completely retain the nonlinear features of MI-EEG...
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| Publicado no: | Comput Intell Neurosci |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Hindawi
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6525943/ https://ncbi.nlm.nih.gov/pubmed/31191631 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2019/4317078 |
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