Adaptive Methods in BCI Research - An Introductory Tutorial
暂无分享,去创建一个
[1] J J Burke. Understanding Kalman Filtering and its Application in Real Time Tracking Systems , 1972 .
[2] G Pfurtscheller,et al. Current trends in Graz Brain-Computer Interface (BCI) research. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[3] Klaus-Robert Müller,et al. Annealed Competition of Experts for a Segmentation and Classification of Switching Dynamics , 1996, Neural Computation.
[4] N. Birbaumer,et al. The thought-translation device (TTD): neurobehavioral mechanisms and clinical outcome , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[5] R. Kalman,et al. New results in linear prediction and filtering theory Trans. AMSE , 1961 .
[6] Cuntai Guan,et al. Digital Signal Processing and Machine Learning , 2009 .
[7] G. Pfurtscheller,et al. Optimal spatial filtering of single trial EEG during imagined hand movement. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[8] E Donchin,et al. Brain-computer interface technology: a review of the first international meeting. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[9] K.-R. Muller,et al. Optimizing Spatial filters for Robust EEG Single-Trial Analysis , 2008, IEEE Signal Processing Magazine.
[10] Alois Schlögl,et al. The Electroencephalogram and the Adaptive Autoregressive Model: Theory and Applications , 2000 .
[11] G. Pfurtscheller,et al. EEG-based discrimination between imagination of right and left hand movement. , 1997, Electroencephalography and clinical neurophysiology.
[12] J. Mourino,et al. Asynchronous BCI and local neural classifiers: an overview of the adaptive brain interface project , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[13] Kazuyuki Aihara,et al. Adapting Spatial Filter Methods for Nonstationary BCIs , 2006 .
[14] Klaus-Robert Müller,et al. Covariate Shift Adaptation by Importance Weighted Cross Validation , 2007, J. Mach. Learn. Res..
[15] Dennis J. McFarland,et al. Design and operation of an EEG-based brain-computer interface with digital signal processing technology , 1997 .
[16] G Pfurtscheller,et al. Adaptive Autoregressive Modeling used for Single-trial EEG Classification - Verwendung eines Adaptiven Autoregressiven Modells für die Klassifikation von Einzeltrial-EEG-Daten , 1997, Biomedizinische Technik. Biomedical engineering.
[17] Klaus-Robert Müller,et al. Spatio-spectral filters for improving the classification of single trial EEG , 2005, IEEE Transactions on Biomedical Engineering.
[18] G Pfurtscheller,et al. Estimating the Mutual Information of an EEG-based Brain-Computer Interface , 2002, Biomedizinische Technik. Biomedical engineering.
[19] S. Haykin,et al. Adaptive Filter Theory , 1986 .
[20] J Wackermann,et al. Towards a quantitative characterisation of functional states of the brain: from the non-linear methodology to the global linear description. , 1999, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[21] Reinhold Scherer,et al. Study of On-Line Adaptive Discriminant Analysis for EEG-Based Brain Computer Interfaces , 2007, IEEE Transactions on Biomedical Engineering.
[22] E. Oja,et al. On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix , 1985 .
[23] G. Pfurtscheller,et al. The BCI competition III: validating alternative approaches to actual BCI problems , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[24] K.-R. Muller,et al. BCI meeting 2005-workshop on BCI signal processing: feature extraction and translation , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[25] R. E. Kalman,et al. A New Approach to Linear Filtering and Prediction Problems , 2002 .
[26] G. Pfurtscheller,et al. Critical Decision-Speed and Information Transfer in the “Graz Brain–Computer Interface” , 2003, Applied psychophysiology and biofeedback.
[27] Masashi Sugiyama,et al. Input-dependent estimation of generalization error under covariate shift , 2005 .
[28] G. Pfurtscheller,et al. On-line EEG classification during externally-paced hand movements using a neural network-based classifier. , 1996, Electroencephalography and clinical neurophysiology.
[29] G. Pfurtscheller,et al. A criterion for adaptive autoregressive models , 2000, Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143).
[30] Reinhold Scherer,et al. A fully on-line adaptive BCI , 2006, IEEE Transactions on Biomedical Engineering.
[31] N. Pop-Jordanova,et al. Spectrum-weighted EEG frequency ("brain-rate") as a quantitative indicator of mental arousal. , 2005, Prilozi.
[32] Victor Solo,et al. Performance analysis of adaptive eigenanalysis algorithms , 1998, IEEE Trans. Signal Process..
[33] Carmen Vidaurre,et al. BioSig: The Free and Open Source Software Library for Biomedical Signal Processing , 2011, Comput. Intell. Neurosci..
[34] B. Hjorth. EEG analysis based on time domain properties. , 1970, Electroencephalography and clinical neurophysiology.
[35] Klaus-Robert Müller,et al. Combined Optimization of Spatial and Temporal Filters for Improving Brain-Computer Interfacing , 2006, IEEE Transactions on Biomedical Engineering.
[36] J. S. Barlow,et al. Changes in EEG mean frequency and spectral purity during spontaneous alpha blocking. , 1990, Electroencephalography and clinical neurophysiology.
[37] Nozer D. Singpurwalla,et al. Understanding the Kalman Filter , 1983 .
[38] Gert Pfurtscheller,et al. Motor imagery and direct brain-computer communication , 2001, Proc. IEEE.
[39] H. Shimodaira,et al. Improving predictive inference under covariate shift by weighting the log-likelihood function , 2000 .
[40] G. Pfurtscheller,et al. Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.
[41] Gert Pfurtscheller,et al. Characterization of four-class motor imagery EEG data for the BCI-competition 2005 , 2005, Journal of neural engineering.
[42] G Pfurtscheller,et al. Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[43] G Pfurtscheller,et al. Adaptive On-line Classification for EEG-based Brain Computer Interfaces with AAR parameters and band power estimates / Adaptive On-line Classification einer EEG-basierenden Gehirn-Computer Schnittstelle mit Adaptive Autoregressiven und Bandleistungsparametern , 2005, Biomedizinische Technik. Biomedical engineering.
[44] A. Schlogl,et al. Information transfer of an EEG-based brain computer interface , 2003, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings..
[45] K. Jellinger. Toward Brain-Computer Interfacing , 2009 .
[46] Matthias Krauledat,et al. Analysis of nonstationarities in EEG signals for improving brain-computer interface performance , 2008 .
[47] R. E. Kalman,et al. New Results in Linear Filtering and Prediction Theory , 1961 .
[48] Terrence J. Sejnowski,et al. Toward Brain-Computer Interfacing (Neural Information Processing) , 2007 .
[49] Rajesh P. N. Rao,et al. Towards adaptive classification for BCI , 2006, Journal of neural engineering.
[50] Klaus-Robert Müller,et al. Combining Features for BCI , 2002, NIPS.