Classification for Different Mental Tasks of EEG Signals Based on Neural Network Ensemble

摘要

the paper puts forward a method that is based on neural network ensemble to classify EEG signals, it uses BP neural network as a classifier to classify the EEG features extracted by the AR parameters. In order to further enhancing the performance of BP neural network classification, it adopts Bagging algorithm to vote on BP neural network classifier with different weightings. Experiments show that the proposed method has a much higher classification rate.