Applying Extreme Learning Machine to classification of EEG BCI

Abstract

Extreme Learning Machine (ELM) is a fast and efficient classifier with single hidden layer feed-forward neural networks. In this paper, the ELM is employed to classify the EEG signals in BCI system, the BCI competition datasets are used to test, the mutual information and classify accuracy are considered as evaluation criteria. Compare with the LDA and SVM, the ELM method could obtain more mutual information and higher classification accuracy.