A novel approach for SEMG signal classification with adaptive local binary patterns
Crossref DOI link: https://doi.org/10.1007/s11517-015-1443-z
Published Online: 2015-12-31
Published Print: 2016-07
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Ertuğrul, Ömer Faruk
Kaya, Yılmaz
Tekin, Ramazan
Text and Data Mining valid from 2015-12-31