Transfer learning (TL) has been proven to be one of the most significant techniques for cross-subject classification in electroencephalogram (EEG)-based brain-computer interfaces (BCI). Hence, it is widely used address challenges cross-session and variability with more accurate intention prediction. In this case, TL utilizes knowledge (signal features) source domain(s) improve target domain. Ho...
