Semi-supervised feature extraction with local temporal regularization for EEG classification

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2011, Pages 75-80

  Tu, Wenting ^a   Sun, Shiliang ^a  

^a EAST CHINA NORMAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMMON SPATIAL PATTERNS; EEG CLASSIFICATION; EIGENVALUE DECOMPOSITION; ELECTROENCEPHALOGRAM SIGNALS; ENERGY FEATURE; ENERGY RATIO; FEATURE EXTRACTOR; GENERALIZATION ABILITY; NONLINEAR EXTENSION; SEMI-SUPERVISED; SMALL TRAINING; SOURCE SIGNALS; SPATIAL FILTERS; TEMPORAL INFORMATION; TEMPORAL REGULARIZATION; TEMPORAL STRUCTURES; UNLABELED DATA;

EIGENVALUES AND EIGENFUNCTIONS; ELECTROENCEPHALOGRAPHY; FEATURE EXTRACTION; INTERFACES (COMPUTER); NEURAL NETWORKS;

BRAIN COMPUTER INTERFACE;

EID: 80054747549     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2011.6033202     Document Type: Conference Paper

References (13)

1. Sun, S.: The Extreme Energy Ratio Criterion for EEG Feature Extraction. Lect. Notes Comput. Sci. 5164, 919-928 (2008)
2. Müller-Gerking, J., Pfurtscheller, G., Flyvbjerg, H.: Designing Optimal Spatial Filters for Single-trial EEG Classification in a Movement Task. Clin. Neurophysiol. 110(5), 787-798 (1999)
3. Schalk, G., Blankertz, B., Chiappa, S., et al.: BCI competition III, http://ida.first.fraunhofer.de/projects/ bci/competition iii/. (2004-2005)
4. Hill, N.J., Lal, T.N., Schröder, M., Hinterberger, T., Widman, G., Elger, C.E., Schölkopf, B., Birbaumer, N.: Classifying Event-Related Desynchronization in EEG, ECoG and MEG Signal. Lect. Notes Comput. Sci. 4174, 404-413 (2006)
5. Belkin, M., Niyogi, P., Sindhwani, V.: Manifold Regularization: A Geometric Framework for Learning from Examples. J. Mach. Learn. Res. 7, 2399-2434 (2006)
6. He, X., Niyogi, P.: Locality Preserving Projections. In: Advances in Neural Information Processing Systems 16, MIT Press, Cambridge, MA (2003)
7. Nunez, P.L., Srinivasan, R., Westdorp, A.F., Wijesinghe, D.M, Tucker, R.B, Cadusch, P,J,: EEG coherency I: Statistics, Reference Electrode, volume conduction, Laplacians, cortical imaging, and interpretation at multiple scale. Electroenceph. Clin. Neurophysiol. 103, 499-515 (1997)
8. Blankertz, B., Curio, G., Müller, K-R.: Classifying Single Trial EEG: Towards Brain Computer Interfacing. NIPS 14, 157-164 (2002)
9. Parra, L.C., Spence, C.D., Gerson, A.D., Sajda, P.: Recipes for the linear analysis of EEG. NeuroImage 28, 326-341 (2005)
10. Sun, S., Zhang, C.: An Optimal Kernel Feature Extractor and Its Application to EEG Signal Classification. Neurocomputing 69, 1743-1748 (2006)
11. Müller, K-R., Mika, S., Rätsch, G., Tsuda, K., Schölkopf, B.: An Introduction to Kernel-Based Learning Algorithms. IEEE Trans. Neural Networks 12, 181-201 (2001)
12. Sun, S., Zhang, C.: Adaptive Feature Extraction for EEG Signal Classification. Med. Biol. Eng. Comput. 44, 931-935 (2006)
13. Millán, J.R: On the Need for On-Line Learning in Brain-Computer Interfaces. IEEE Int. Conf. Neural. Netw. Conf. Proc. 4, 2877-2882 (2004)