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Bayesian inference in the uncertain EEG problem including local information and a sensor correlation matrix

Rob De Staelen (UGent) , Guillaume Crevecoeur (UGent) , Tineke Goessens (UGent) and Marian Slodicka (UGent)
Author
Organization
Keywords
Correlation, HUMAN-BRAIN, CHAOS, Inverse problem, Bayesian inference, EEG, Polynomial Chaos, Conductivity

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Citation

Please use this url to cite or link to this publication:

MLA
De Staelen, Rob, Guillaume Crevecoeur, Tineke Goessens, et al. “Bayesian Inference in the Uncertain EEG Problem Including Local Information and a Sensor Correlation Matrix.” JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 252 (2013): 177–182. Print.
APA
De Staelen, Rob, Crevecoeur, G., Goessens, T., & Slodicka, M. (2013). Bayesian inference in the uncertain EEG problem including local information and a sensor correlation matrix. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 252, 177–182.
Chicago author-date
De Staelen, Rob, Guillaume Crevecoeur, Tineke Goessens, and Marian Slodicka. 2013. “Bayesian Inference in the Uncertain EEG Problem Including Local Information and a Sensor Correlation Matrix.” Journal of Computational and Applied Mathematics 252: 177–182.
Chicago author-date (all authors)
De Staelen, Rob, Guillaume Crevecoeur, Tineke Goessens, and Marian Slodicka. 2013. “Bayesian Inference in the Uncertain EEG Problem Including Local Information and a Sensor Correlation Matrix.” Journal of Computational and Applied Mathematics 252: 177–182.
Vancouver
1.
De Staelen R, Crevecoeur G, Goessens T, Slodicka M. Bayesian inference in the uncertain EEG problem including local information and a sensor correlation matrix. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS. 2013;252:177–82.
IEEE
[1]
R. De Staelen, G. Crevecoeur, T. Goessens, and M. Slodicka, “Bayesian inference in the uncertain EEG problem including local information and a sensor correlation matrix,” JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, vol. 252, pp. 177–182, 2013.
@article{3051638,
  author       = {De Staelen, Rob and Crevecoeur, Guillaume and Goessens, Tineke and Slodicka, Marian},
  issn         = {0377-0427},
  journal      = {JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS},
  keywords     = {Correlation,HUMAN-BRAIN,CHAOS,Inverse problem,Bayesian inference,EEG,Polynomial Chaos,Conductivity},
  language     = {eng},
  pages        = {177--182},
  title        = {Bayesian inference in the uncertain EEG problem including local information and a sensor correlation matrix},
  url          = {http://dx.doi.org/10.1016/j.cam.2012.12.016},
  volume       = {252},
  year         = {2013},
}

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