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EEG Feature Selection via Stacked Deep Embedded Regression With Joint Sparsity
In the field of brain-computer interface (BCI), selecting efficient and robust features is very seductive for artificial intelligence (AI)-assisted clinical diagnosis. In this study, based on an embedded feature selection model, we construct a stacked deep structure for feature selection in a layer-...
Autores principales: | Jiang, Kui, Tang, Jiaxi, Wang, Yulong, Qiu, Chengyu, Zhang, Yuanpeng, Lin, Chuang |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7423875/ https://www.ncbi.nlm.nih.gov/pubmed/32848581 http://dx.doi.org/10.3389/fnins.2020.00829 |
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