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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Detalles Bibliográficos
Autores principales: Li, Mingai, Xi, Hongwei, Zhu, Xiaoqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525943/
https://www.ncbi.nlm.nih.gov/pubmed/31191631
http://dx.doi.org/10.1155/2019/4317078

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525943/
https://www.ncbi.nlm.nih.gov/pubmed/31191631
http://dx.doi.org/10.1155/2019/4317078

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