SSVEP recognition using common feature analysis in brain–computer interface
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Xingyu Wang | Andrzej Cichocki | Guoxu Zhou | Jing Jin | Yu Zhang | A. Cichocki | Xingyu Wang | Jing Jin | Yu Zhang | Guoxu Zhou
[1] H. Knutsson,et al. Detection of neural activity in functional MRI using canonical correlation analysis , 2001, Magnetic resonance in medicine.
[2] Xiaorong Gao,et al. Design and implementation of a brain-computer interface with high transfer rates , 2002, IEEE Transactions on Biomedical Engineering.
[3] G. Pfurtscheller,et al. Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.
[4] Xiaorong Gao,et al. A BCI-based environmental controller for the motion-disabled. , 2003, IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[5] Reinhold Scherer,et al. Steady-state visual evoked potential (SSVEP)-based communication: impact of harmonic frequency components , 2005, Journal of neural engineering.
[6] E. Donchin,et al. A P300-based brain–computer interface: Initial tests by ALS patients , 2006, Clinical Neurophysiology.
[7] Wei Wu,et al. Frequency Recognition Based on Canonical Correlation Analysis for SSVEP-Based BCIs , 2006, IEEE Transactions on Biomedical Engineering.
[8] Shangkai Gao,et al. A practical VEP-based brain-computer interface. , 2006, IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[9] Clemens Brunner,et al. Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks , 2006, NeuroImage.
[10] Ivan Volosyak,et al. Multiple Channel Detection of Steady-State Visual Evoked Potentials for Brain-Computer Interfaces , 2007, IEEE Transactions on Biomedical Engineering.
[11] Yuanqing Li,et al. Joint feature re-extraction and classification using an iterative semi-supervised support vector machine algorithm , 2008, Machine Learning.
[12] Touradj Ebrahimi,et al. An efficient P300-based brain–computer interface for disabled subjects , 2008, Journal of Neuroscience Methods.
[13] J. Wolpaw,et al. Towards an independent brain–computer interface using steady state visual evoked potentials , 2008, Clinical Neurophysiology.
[14] Dezhong Yao,et al. Frequency detection with stability coefficient for steady-state visual evoked potential (SSVEP)-based BCIs. , 2008, Journal of neural engineering.
[15] Yijun Wang,et al. Brain-Computer Interfaces Based on Visual Evoked Potentials , 2008, IEEE Engineering in Medicine and Biology Magazine.
[16] Yuanqing Li,et al. A self-training semi-supervised SVM algorithm and its application in an EEG-based brain computer interface speller system , 2008, Pattern Recognit. Lett..
[17] Gernot R. Müller-Putz,et al. Comparison of DFT and lock-in amplifier features and search for optimal electrode positions in SSVEP-based BCI , 2008, Journal of Neuroscience Methods.
[18] Xiaorong Gao,et al. An online multi-channel SSVEP-based brain–computer interface using a canonical correlation analysis method , 2009, Journal of neural engineering.
[19] Liqing Zhang,et al. Bilateral adaptation and neurofeedback for brain computer interface system , 2010, Journal of Neuroscience Methods.
[20] B. Allison,et al. BCI Demographics: How Many (and What Kinds of) People Can Use an SSVEP BCI? , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[21] Yuanqing Li,et al. An EEG-Based BCI System for 2-D Cursor Control by Combining Mu/Beta Rhythm and P300 Potential , 2010, IEEE Transactions on Biomedical Engineering.
[22] Xingyu Wang,et al. Multiway Canonical Correlation Analysis for Frequency Components Recognition in SSVEP-Based BCIs , 2011, ICONIP.
[23] Po-Lei Lee,et al. Frequency recognition in an SSVEP-based brain computer interface using empirical mode decomposition and refined generalized zero-crossing , 2011, Journal of Neuroscience Methods.
[24] Xiaorong Gao,et al. Enhancing the classification accuracy of steady-state visual evoked potential-based brain–computer interfaces using phase constrained canonical correlation analysis , 2011, Journal of neural engineering.
[25] Brendan Z. Allison,et al. How Many People Could Use an SSVEP BCI? , 2012, Front. Neurosci..
[26] Chang-Hwan Im,et al. Development of an SSVEP-based BCI spelling system adopting a QWERTY-style LED keyboard , 2012, Journal of Neuroscience Methods.
[27] Andrzej Cichocki,et al. Common and Individual Features Analysis: Beyond Canonical Correlation Analysis , 2012, ArXiv.
[28] A. Cichocki,et al. A novel BCI based on ERP components sensitive to configural processing of human faces , 2012, Journal of neural engineering.
[29] Jing Wang,et al. Steady-State Motion Visual Evoked Potentials Produced by Oscillating Newton's Rings: Implications for Brain-Computer Interfaces , 2012, PloS one.
[30] D. Yao,et al. Multiple Frequencies Sequential Coding for SSVEP-Based Brain-Computer Interface , 2012, PloS one.
[31] Heikki Lyytinen,et al. Benefits of Multi-Domain Feature of mismatch Negativity Extracted by Non-Negative Tensor Factorization from EEG Collected by Low-Density Array , 2012, Int. J. Neural Syst..
[32] Tapani Ristaniemi,et al. Multi-Domain Feature Extraction for Small Event-Related potentials through Nonnegative Multi-Way Array Decomposition from Low Dense Array EEG , 2013, Int. J. Neural Syst..
[33] Fanglin Chen,et al. A novel hybrid BCI speller based on the incorporation of SSVEP into the P300 paradigm , 2013, Journal of neural engineering.
[34] Andrzej Cichocki,et al. L1-Regularized Multiway Canonical Correlation Analysis for SSVEP-Based BCI , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[35] Xingyu Wang,et al. Spatial-Temporal Discriminant Analysis for ERP-Based Brain-Computer Interface , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[36] Yangsong Zhang,et al. Multivariate synchronization index for frequency recognition of SSVEP-based brain–computer interface , 2014, Journal of Neuroscience Methods.
[37] Xingyu Wang,et al. Frequency Recognition in SSVEP-Based BCI using Multiset Canonical Correlation Analysis , 2013, Int. J. Neural Syst..
[38] Xingyu Wang,et al. Aggregation of Sparse Linear Discriminant analyses for Event-Related potential Classification in Brain-Computer Interface , 2014, Int. J. Neural Syst..