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Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso

Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs). Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wr...

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Publicat a:Biomed Res Int
Autors principals: Wang, Jin-Jia, Xue, Fang, Li, Hui
Format: Artigo
Idioma:Inglês
Publicat: Hindawi Publishing Corporation 2015
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Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC4354735/
https://ncbi.nlm.nih.gov/pubmed/25802861
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2015/703768
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