Feature optimization based on improved novel global harmony search algorithm for motor imagery electroencephalogram classification

HIGHLIGHTS

  • who: Bin Shi from the Sejong University, South Korea and Technology, China have published the paper: Feature optimization based on improved novel global harmony search algorithm for motor imagery electroencephalogram classification, in the Journal: (JOURNAL)
  • what: In the work , the INGHS algorithm is introduced in this article to solve the combined frequency-time optimization problem for more accurate MI-related EEG classification. In this study, all experimental simulations are implemented by using MATLABR2019b on a Windows personal computer with Core i5-9500H 3.00 GHz CPU and RAM 8.00 GB. The main reason is . . .

     

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