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Accurate classification of left and right hand motor imagery of EEG is an important issue in brain-computer interface (BCI). Here, discrete wavelet transform was firstly applied to extract the features of left and right hand motor imagery in EEG. Secondly, Fisher Linear Discriminant Analysis was used with two different threshold calculation methods and obtained good misclassification rate. We also...
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