Research on the Neural Dipole Localization Using a Method Combining SVM with Nonlinear Dimensionality Reduction
Electroencephalogram (EEG) source localization is well known as an import inverse problem of electrophysiology. In order to improve the accuracy of inverse calculation from EEG signal, a new method combining multidimensional SVR with Nonlinear dimensionality reduction was proposed. In our study, the ISOMAP algorithm was firstly used to find the low dimensional manifolds from high dimensional EEG signal. Then, a new method of Multidimensional Support Vector Regression (MSVR) with similar iterative re-weight least square (IRWLS) was applied to discover the parameters of EEG signals. In our experiments, EEG signals of epileptic spike were adopted as the objects. The satisfactory results were obtained.
EEG inverse problem multidimensional support vector regression ISOMAP IRWLS Epileptic spike
Jianwei LI Youhua WANG Guilong ZONG Qing WU
Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Hebei University of Technology Tianjin,300130,China
国际会议
北京
英文
1-4
2009-06-11（万方平台首次上网日期，不代表论文的发表时间）