These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

178 related articles for article (PubMed ID: 21493037)

  • 1. Bayesian inference for an adaptive Ordered Probit model: an application to Brain Computer Interfacing.
    Yoon JW; Roberts SJ; Dyson M; Gan JQ
    Neural Netw; 2011 Sep; 24(7):726-34. PubMed ID: 21493037
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Adaptive classification for Brain Computer Interface systems using Sequential Monte Carlo sampling.
    Yoon JW; Roberts SJ; Dyson M; Gan JQ
    Neural Netw; 2009 Nov; 22(9):1286-94. PubMed ID: 19608382
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation.
    Sykacek P; Roberts SJ; Stokes M
    IEEE Trans Biomed Eng; 2004 May; 51(5):719-27. PubMed ID: 15132497
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Comparison of linear, nonlinear, and feature selection methods for EEG signal classification.
    Garrett D; Peterson DA; Anderson CW; Thaut MH
    IEEE Trans Neural Syst Rehabil Eng; 2003 Jun; 11(2):141-4. PubMed ID: 12899257
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An extended EM algorithm for joint feature extraction and classification in brain-computer interfaces.
    Li Y; Guan C
    Neural Comput; 2006 Nov; 18(11):2730-61. PubMed ID: 16999577
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Different classification techniques considering brain computer interface applications.
    Rezaei S; Tavakolian K; Nasrabadi AM; Setarehdan SK
    J Neural Eng; 2006 Jun; 3(2):139-44. PubMed ID: 16705270
    [TBL] [Abstract][Full Text] [Related]  

  • 7. EEG-based motor imagery classification using neuro-fuzzy prediction and wavelet fractal features.
    Hsu WY
    J Neurosci Methods; 2010 Jun; 189(2):295-302. PubMed ID: 20381529
    [TBL] [Abstract][Full Text] [Related]  

  • 8. An empirical bayesian framework for brain-computer interfaces.
    Lei X; Yang P; Yao D
    IEEE Trans Neural Syst Rehabil Eng; 2009 Dec; 17(6):521-9. PubMed ID: 19622442
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A novel criterion of wavelet packet best basis selection for signal classification with application to brain-computer interfaces.
    Vautrin D; Artusi X; Lucas MF; Farina D
    IEEE Trans Biomed Eng; 2009 Nov; 56(11 Pt 2):2734-8. PubMed ID: 19651550
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine learning for real-time single-trial EEG-analysis: from brain-computer interfacing to mental state monitoring.
    Müller KR; Tangermann M; Dornhege G; Krauledat M; Curio G; Blankertz B
    J Neurosci Methods; 2008 Jan; 167(1):82-90. PubMed ID: 18031824
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Cognitive tasks for driving a brain-computer interfacing system: a pilot study.
    Curran E; Sykacek P; Stokes M; Roberts SJ; Penny W; Johnsrude I; Owen AM
    IEEE Trans Neural Syst Rehabil Eng; 2004 Mar; 12(1):48-54. PubMed ID: 15068187
    [TBL] [Abstract][Full Text] [Related]  

  • 12. xDAWN algorithm to enhance evoked potentials: application to brain-computer interface.
    Rivet B; Souloumiac A; Attina V; Gibert G
    IEEE Trans Biomed Eng; 2009 Aug; 56(8):2035-43. PubMed ID: 19174332
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Time-frequency analysis of EEG asymmetry using bivariate empirical mode decomposition.
    Park C; Looney D; Kidmose P; Ungstrup M; Mandic DP
    IEEE Trans Neural Syst Rehabil Eng; 2011 Aug; 19(4):366-73. PubMed ID: 21342855
    [TBL] [Abstract][Full Text] [Related]  

  • 14. [Bayesian classifier for brain-computer interface based on mental representation of movements].
    Bobrov PD; Korshakov AV; Roshchin VIu; Frolov AA
    Zh Vyssh Nerv Deiat Im I P Pavlova; 2012; 62(1):89-99. PubMed ID: 22567990
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Sequential Monte Carlo point-process estimation of kinematics from neural spiking activity for brain-machine interfaces.
    Wang Y; Paiva AR; Príncipe JC; Sanchez JC
    Neural Comput; 2009 Oct; 21(10):2894-930. PubMed ID: 19548797
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Neural network classification of autoregressive features from electroencephalogram signals for brain-computer interface design.
    Huan NJ; Palaniappan R
    J Neural Eng; 2004 Sep; 1(3):142-50. PubMed ID: 15876633
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Bispectrum-based feature extraction technique for devising a practical brain-computer interface.
    Shahid S; Prasad G
    J Neural Eng; 2011 Apr; 8(2):025014. PubMed ID: 21436530
    [TBL] [Abstract][Full Text] [Related]  

  • 18. sw-SVM: sensor weighting support vector machines for EEG-based brain-computer interfaces.
    Jrad N; Congedo M; Phlypo R; Rousseau S; Flamary R; Yger F; Rakotomamonjy A
    J Neural Eng; 2011 Oct; 8(5):056004. PubMed ID: 21817778
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A user-friendly SSVEP-based brain-computer interface using a time-domain classifier.
    Luo A; Sullivan TJ
    J Neural Eng; 2010 Apr; 7(2):26010. PubMed ID: 20332551
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A review of classification algorithms for EEG-based brain-computer interfaces.
    Lotte F; Congedo M; Lécuyer A; Lamarche F; Arnaldi B
    J Neural Eng; 2007 Jun; 4(2):R1-R13. PubMed ID: 17409472
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.