Before revision:  This study aims to develop a cross-subject transferring approach to reduce the need for  training data from a test user . Study results showed that a new least-squares transformation (LST) method was able to significantly reduce the training templates required for a 40-class SSVEP BCI.
After revision:  This study aims to develop a cross-subject transferring approach to reduce the need for training data from a test user . Study results showed that a new least-squares transformation (LST) method . Study results show the capability of the LST in reducing the number of training templates required for a 40-class SSVEP BCI.