In this paper, a self-adaptive subgraph generation algorithm for EEG channel selection (SSGE), built on the base of graph convolution network (GCN), was ...
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In this work, we proposed a self-adaptive subgraph generation algorithm for EEG channel selection. A novel message passing mechanism was designed to ...
Aug 25, 2024 · In this paper, weak periodic signals detected in the EEG signals were analysed for each region of the brain and its relationships with ...
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Self-adaptive evolutionary algorithm, which can construct mutation strategies in the strategy pool based on the experience of producing solutions for selecting ...
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Aug 1, 2015 · In this paper, we survey the recent developments in the field of EEG channel selection methods along with their applications and classify these methods ...
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Aug 15, 2024 · We introduce a novel adaptive method for extracting node features from EEG signals utilizing a distinctive task-induced self-supervised learning technique.
We review several existing works to find the most promising MI-based EEG channel selection algorithms and associated classification methodologies on various ...
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Unranked. Kui Zhao, Yanqing Kang, Jinru Wu, Enze Shi, Di Zhu, Shu Zhang A Self-Adaptive Subgraph Generation Algorithm for EEG Channel Selection.ISBI 2024: 1 ...
Dec 10, 2024 · Therefore, channel selection can improve BCI performance and contribute to user convenience. Additionally, cross-subject generalization is a key ...
In this paper, we propose a subject-independent emotion recognition model based on adaptive extraction of layer structure based on frequency bands (BFE-Net).
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