Mar 1, 2024 · In this paper, we propose an EEG selection framework based on bidirectional long short-term memory network (BiLSTM) and non-dominated sorting genetic algorithm ...
Nov 21, 2024 · In this paper, we propose an EEG selection framework based on bidirectional long short-term memory network (BiLSTM) and non-dominated sorting ...
The EEG data is first identified using BiLSTM, followed by optimization of the results using NSGAII, and continuous iteration to arrive at the optimal channel ...
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This article proposes an approach to select EEG channels based on EEG shapelet transformation, aiming to reduce the setup time and inconvenience for subjects.
For selecting channels or features, the NSGA-II algorithm employs a dynamic approach to select channels or features based on predefined objectives, maximizing ...
Oct 22, 2024 · In this paper, the NSGA-II algorithm is applied to get the optimum set of EEG channels for seizure prediction. The NSGA-II algorithm identifies ...
We present a multi-objective optimization method for electroencephalographic (EEG) channel selection based on the non-dominated sorting genetic algorithm (NSGA)
Missing: BiLSTM | Show results with:BiLSTM
Jul 1, 2022 · This study proposes a comparative analysis of channel signals exploiting the Deep Learning (DL) technique and a public dataset to locate the most discriminant ...
Dec 17, 2024 · The effect of the statistical significance-based feature selection method was investigated for each feature set on binary-class and multi-class ...
Sep 6, 2024 · Abstract: The integration of Genetic Algorithms (GAs) into Serious Games (SGs) has gained traction as a method.