Efficient Feature Learning Model of Motor Imagery EEG Signals with L1-Norm and Weighted Fusion
Efficient Feature Learning Model of Motor Imagery EEG Signals with L1-Norm and Weighted Fusion
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Publisher
Switzerland: MDPI AG
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Language
English
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Switzerland: MDPI AG
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Brain-computer interface (BCI) for motor imagery is an advanced technology used in the field of medical rehabilitation. However, due to the poor accuracy of electroencephalogram feature classification, BCI systems often misrecognize user commands. Although many state-of-the-art feature selection methods aim to enhance classification accuracy, they...
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Full title
Efficient Feature Learning Model of Motor Imagery EEG Signals with L1-Norm and Weighted Fusion
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TN_cdi_doaj_primary_oai_doaj_org_article_bae67da8746647cab30771701785b5e0
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_bae67da8746647cab30771701785b5e0
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ISSN
2079-6374
E-ISSN
2079-6374
DOI
10.3390/bios14050211
