Probabilistic Common Spatial Patterns for Multichannel EEG Analysis

@article{Wu2015ProbabilisticCS,
  title={Probabilistic Common Spatial Patterns for Multichannel EEG Analysis},
  author={Wei Wu and Zhe Chen and Xiaorong Gao and Yuanqing Li and Emery N. Brown and Shangkai Gao},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2015},
  volume={37},
  pages={639-653}
}
Common spatial patterns (CSP) is a well-known spatial filtering algorithm for multichannel electroencephalogram (EEG) analysis. In this paper, we cast the CSP algorithm in a probabilistic modeling setting. Specifically, probabilistic CSP (P-CSP) is proposed as a generic EEG spatio-temporal modeling framework that subsumes the CSP and regularized CSP algorithms. The proposed framework enables us to resolve the overfitting issue of CSP in a principled manner. We derive statistical inference… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 59 references

FLD. Electroencephalography: Basic Principles, Clinical Applications, and Related Fields

  • Niedermeyer, Silva
  • 2004
Highly Influential
7 Excerpts

Scale mixtures of normal distributions

  • DF Andrews, CL Mallows
  • J Roy Statist Soc
  • 1974
Highly Influential
6 Excerpts

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