EMOTION RECOGNITION OF EEG BASED ON OPTIMAL VARIATIONAL MODE DECOMPOSITION
In order to improve the accuracy and reliability of EEG emotion recognition,a recognition method of EGG emotion based on optimal variational mode decomposition(VMD)is proposed.The rhythm signal of emotional EEG was decomposed by VMD,and the krill swarm optimization(KH)was introduced to search the optimal decomposition layer number and punishment factor of VMD.The average energy and power spectral density were extracted from the decomposed intrinsic modal component(IMFs)as features.The XGBoost algorithm was used for classification.The experimental results show that compared with EMD and EEMD,the classification accuracy of this method in DEAP dataset reaches 91.02％,which can more effectively extract EEG emotional features,and provide a new method for the study of EEG emotion recognition.
万方数据
维普
