FEATURE EXTRACTION OF MOTOR IMAGERY EEG SIGNALS BASED ON MULTI-SCALE RECURRENCE PLOT AND SDA

When recognizing multi-class motor imagery electoencephalogram(EEG) signals directly using stacked denoising autoencoders (SDA),it is difficult to fully train the weights due to the small samplesize, which results in poor classification effect.