Online prediction of EEG based on KRLST algorithm  

作　　者：Lian Zhaoyang Duan Lijuan Chen Juncheng Qiao Yuanhua Miao Jun 连召洋;Duan Lijuan;Chen Juncheng;Qiao Yuanhua;Miao Jun(Faculty of Information Technology,Beijing University of Technology,Beijing 100124,P.R.China;Beijing Key Laboratory of Trusted Computing,Beijing 100124,P.R.China;National Engineering Laboratory for Key Technologies of Information Security Level Protection,Beijing 100124,P.R.China;Faculty of Sciences,Beijing University of Technology,Beijing 100124,P.R.China;Beijing Key Laboratory of Internet Culture and Digital Dissemination Research,School of Computer Science,Beijing Information Science and Technology University,Beijing 100101,P.R.China)

机构地区：[1]Faculty of Information Technology,Beijing University of Technology,Beijing 100124,P.R.China [2]Beijing Key Laboratory of Trusted Computing,Beijing 100124,P.R.China [3]National Engineering Laboratory for Key Technologies of Information Security Level Protection,Beijing 100124,P.R.China [4]Faculty of Sciences,Beijing University of Technology,Beijing 100124,P.R.China [5]Beijing Key Laboratory of Internet Culture and Digital Dissemination Research,School of Computer Science,Beijing Information Science and Technology University,Beijing 100101,P.R.China

出　　处：《High Technology Letters》2021年第4期357-364,共8页高技术通讯（英文版）

基　　金：the National Natural Science Foundation of China(No.61672070,62173010);the Beijing Municipal Natural Science Foundation(No.4192005,4202025);the Beijing Municipal Education Commission Project(No.KM201910005008,KM201911232003);the Beijing Innovation Center for Future Chips(No.KYJJ2018004).

摘　　要：Kernel adaptive algorithm is an extension of adaptive algorithm in nonlinear,and widely used in the field of non-stationary signal processing.But the distribution of classic data sets seems relatively regular and simple in time series.The distribution of the electroencephalograph(EEG)signal is more randomness and non-stationarity,so online prediction of EEG signal can further verify the robustness and applicability of kernel adaptive algorithms.What’s more,the purpose of modeling and analyzing the time series of EEG signals is to discover and extract valuable information,and to reveal the internal relations of EEG signals.The time series prediction of EEG plays an important role in EEG time series analysis.In this paper,kernel RLS tracker(KRLST)is presented to online predict the EEG signals of motor imagery and compared with other 13 kernel adaptive algorithms.The experimental results show that KRLST algorithm has the best effect on the brain computer interface(BCI)dataset.

关 键 词：brain computer interface(BCI) kernel adaptive algorithm online prediction of electroencephalograph(EEG) 

分 类 号：TN911.7[电子电信—通信与信息系统] R318[电子电信—信息与通信工程]