Before revision:  The proposed least-squares transformation (LST) method was able to significantly reduce the training templates required for TRCA-based SSVEP detection on a 40-class SSVEP dataset from 8 subjects. This study shed light on plug-and-play high speed SSVEP-based BCIfor further practical applications .
After revision:  The proposed least-squares transformation (LST) method was able to significantly reduce the training templates required for TRCA-based SSVEP detection on a 40-class TRCA-based SSVEP BCI. The LST method may lead to numerous practical applications of plug-and-play high speed SSVEP-based BCIfor further practical applications .