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arXiv · 1212.4347

Bayesian Group Nonnegative Matrix Factorization for EEG Analysis

Bonggun Shin·Alice Oh
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Abstract

We propose a generative model of a group EEG analysis, based on appropriate kernel assumptions on EEG data. We derive the variational inference update rule using various approximation techniques. The proposed model outperforms the current state-of-the-art algorithms in terms of common pattern extraction. The validity of the proposed model is tested on the BCI competition dataset.

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Bonggun Shin, Alice Oh. 2012-12-18. Bayesian Group Nonnegative Matrix Factorization for EEG Analysis. https://arxiv.org/abs/1212.4347

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