| Title: | GS6-3 An Optimization of Spatio-Spectral Filter Bank Design for EEG Classification |
|---|---|
| Publication: | ICAROB2016 |
| Volume: | 21 |
| Pages: | 397-400 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2016.GS6-3 |
| Author(s): | Masanao Obayashi, Takuya Geshi, Takashi Kuremoto, Shingo Mabu |
| Publication Date: | January 29, 2016 |
| Keywords: | spatio-spectral filter, EEG, classification, .optimization, mutual information, common spatial filter |
| Abstract: | How to select the appropriate frequency band to classify EEG signal by motor imagery is discussed in this paper. Our proposal is an improvement of the conventional Bayesian Spatio-Spectral Filter Optimization (BSSFO). Defect of BSSFO is on the way to generate the renewal particle of the filter bank, such a random number generation. To avoid a local optimum, an evolutional update method of particles is introduced. It is shown that performance of the EEG classification ability is improved. |
| PDF File: | https://alife-robotics.co.jp/members2016/icarob/data/papers/GS/GS6-3.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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