caa a22 4500 44529499X CHVBK 20180317142539.0 cr unu---uuuuu 170323e20101201xx s 000 0 eng 10.1007/s11571-010-9125-x doi (NATIONALLICENCE)springer-10.1007/s11571-010-9125-x Generalized optimal spatial filtering using a kernel approach with application to EEG classification [Elektronische Daten] [Qibin Zhao, Tomasz Rutkowski, Liqing Zhang, Andrzej Cichocki] Common spatial patterns (CSP) has been widely used for finding the linear spatial filters which are able to extract the discriminative brain activities between two different mental tasks. However, the CSP is difficult to capture the nonlinearly clustered structure from the non-stationary EEG signals. To relax the presumption of strictly linear patterns in the CSP, in this paper, a generalized CSP (GCSP) based on generalized singular value decomposition (GSVD) and kernel method is proposed. Our method is able to find the nonlinear spatial filters which are formulated in the feature space defined by a nonlinear mapping through kernel functions. Furthermore, in order to overcome the overfitting problem, the regularized GCSP is developed by adding the regularized parameters. The experimental results demonstrate that our method is an effective nonlinear spatial filtering method. Springer Science+Business Media B.V., 2010 EEG nationallicence BCI nationallicence Kernel method nationallicence CSP nationallicence Zhao Qibin Laboratory for Advanced Brain Signal Processing, Brain Science Institute, RIKEN, Saitama, Japan aut Rutkowski Tomasz Laboratory for Advanced Brain Signal Processing, Brain Science Institute, RIKEN, Saitama, Japan aut Zhang Liqing MOE-Microsoft Laboratory for Intelligent Computing and Intelligent Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China aut Cichocki Andrzej Laboratory for Advanced Brain Signal Processing, Brain Science Institute, RIKEN, Saitama, Japan aut Cognitive Neurodynamics Springer Netherlands 4/4(2010-12-01), 355-358 1871-4080 4:4<355 2010 4 11571 https://doi.org/10.1007/s11571-010-9125-x text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11571-010-9125-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhao Qibin Laboratory for Advanced Brain Signal Processing, Brain Science Institute, RIKEN, Saitama, Japan aut NATIONALLICENCE 700 1- Rutkowski Tomasz Laboratory for Advanced Brain Signal Processing, Brain Science Institute, RIKEN, Saitama, Japan aut NATIONALLICENCE 700 1- Zhang Liqing MOE-Microsoft Laboratory for Intelligent Computing and Intelligent Systems, Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China aut NATIONALLICENCE 700 1- Cichocki Andrzej Laboratory for Advanced Brain Signal Processing, Brain Science Institute, RIKEN, Saitama, Japan aut NATIONALLICENCE 773 0- Cognitive Neurodynamics Springer Netherlands 4/4(2010-12-01), 355-358 1871-4080 4:4<355 2010 4 11571 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer