Classification for Different Mental Tasks of EEG Signals Based on Neural Network Ensemble
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.
EEG BP neural network AR parameters Bagging algorithm
Huaping Jia
Department of Computer Science Weinan Teachers University Weinan,P.R.China
国际会议
太原
英文
583-585
2011-02-26(万方平台首次上网日期,不代表论文的发表时间)