Person identification using EEG channel selection with hybrid flower pollination algorithm
作者：
Highlights：
• Hybridizing Flower Pollination with hill climbing (FPAc) for EEG-based person identification.
• FPAc is used to select the optimal EEG channels which can provides high accuracy.
• FPAc tested using standard EEG dataset, namely, EEG motor movement/imagery dataset.
• The results of FPAc are compared with standard FPA and with other state-of-arts.
• Effect of FPAc on the performance of EEG channels selection is studied and shows significant improvements.
摘要
•Hybridizing Flower Pollination with hill climbing (FPAc) for EEG-based person identification.•FPAc is used to select the optimal EEG channels which can provides high accuracy.•FPAc tested using standard EEG dataset, namely, EEG motor movement/imagery dataset.•The results of FPAc are compared with standard FPA and with other state-of-arts.•Effect of FPAc on the performance of EEG channels selection is studied and shows significant improvements.
论文关键词：EEG,Biometric,Channel selection,Flower pollination algorithm,β-hill climbing
论文评审过程：Received 6 July 2019, Revised 7 March 2020, Accepted 21 April 2020, Available online 26 April 2020, Version of Record 1 May 2020.
论文官网地址：https://doi.org/10.1016/j.patcog.2020.107393
