Data fusion for paroxysmal events' classification from EEG.

Abstract : Spatiotemporal analysis of electroencephalography is commonly used for classification of events since it allows capturing dependencies across channels. The significant increase of feature vector dimensionality however introduce noise and thus it does not allow the classification models to be trained using a limited number of samples usually available in clinical studies.
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https://hal.inria.fr/hal-01426373
Contributor : Evangelia Zacharaki <>
Submitted on : Wednesday, January 4, 2017 - 2:23:36 PM
Last modification on : Thursday, February 7, 2019 - 5:51:21 PM

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Evangelia Pippa, Evangelia I Zacharaki, Michael Koutroumanidis, Vasileios Megalooikonomou. Data fusion for paroxysmal events' classification from EEG.. Journal of Neuroscience Methods, Elsevier, 2017, 275, pp.55-65. ⟨10.1016/j.jneumeth.2016.10.004⟩. ⟨hal-01426373⟩

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