An Optimization of Spatio-Spectral Filter Bank Design for EEG Classification

DOI

10.2991/jrnal.2016.2.4.3How to use a DOI?

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Masanao Obayashi
AU  - Takuya Geshi
AU  - Takashi Kuremoto
AU  - Shingo Mabu
PY  - 2016
DA  - 2016/03/01
TI  - An Optimization of Spatio-Spectral Filter Bank Design for EEG Classification
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 217
EP  - 220
VL  - 2
IS  - 4
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2016.2.4.3
DO  - 10.2991/jrnal.2016.2.4.3
ID  - Obayashi2016
ER  -