  Nowadays, Brain Computer Interface has an important role in the life quality
of parallelized people. However, this technique is mainly affected by the
quality of the recorded signal in each trial. This problem could be solved by
rejecting low-quality trials. But developing the processing based on the
recorded signal from the brain, which is a mixture of the target signal plus
noise and artifact, would not be favorable in situations that all trials have
low quality. This paper solves this problem by presenting a new fast algorithm
for separating recorded source signals. Results indicate the improvement in
classification accuracy of the proposed method compared with the classification
accuracy of processing on the recorded mixture signal.
