In brain-computer interfaces (BCIs), a feature selection approach using an adaptive genetic algorithm (AGA) is described in this paper.
In brain-computer interfaces (BCIs), a feature selection approach using an adaptive genetic algorithm (AGA) is described in this paper.
Automated Feature Selection Based on Adaptive Genetic Algorithm for Brain-Computer Interfaces · Wu Ting, Y. Guozheng, +1 author. Sun Hong · Published 2008 ...
In this paper we propose a feature selection approach based on a genetic algorithm (GA) to pick most promising channels of EEG signals for the ...
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In brain-computer interfaces (BCIs), a feature selection approach using a gene optimization algorithm (GO) is described in this paper. GO algorithm realizes ...
Based upon EEG data of an existing BCI system, we present a wrapper method for the automated selection of features. The proposed method combines a genetic ...
This paper presents a new feature selection method that improves left/right hand movement identification of a motor imagery brain-computer interface, based on ...
Exploring feature selection and classification techniques to improve the performance of an electroencephalography-based motor imagery brain–computer interface ...
Aug 13, 2018 · A novel signal processing framework for a binary motor imagery-based BCI system (MI–BCI) is proposed in this paper.
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A new feature selection method is presented that improves left/right hand movement identification of a motor imagery brain-computer interface, based on ...