In this paper, the paradigm of the intention of speed changes from EEG signals with Riemannian classifiers methods is studied in 10 subjects.
Abstract— In this paper, the paradigm of the intention of speed changes from EEG signals with Riemannian classifiers methods is studied in 10 subjects.
Aug 2, 2024 · This paper presents a comprehensive review of recent advancements in the integration of deep learning with Riemannian geometry to enhance EEG ...
Dec 8, 2022 · Intuitively, this procedure serves as denoisingon the spatial covariancematrices and leads to more robust estimates of the spatial covariance.
Jul 28, 2017 · The use of Riemannian geometry for classification and detection of empirical data is relatively new, but has spread rapidly driven by practical ...
Jul 19, 2024 · This paper presents a comprehensive review of recent advancements in the integration of deep learning with Riemannian geometry to enhance EEG signal decoding ...
In this article, we prove the capabilities of our SPDTransNet model, particularly its adaptability to multi-dataset tasks, within the context of EEG sleep stage ...
Riemannian classification analysis for model EEG intention speed patterns Conference Poster 2022 Congress communication uri icon.
Dimension selection for EEG classification in the SPD ...
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Nov 4, 2023 · This paper proposes a novel dimension selection method named dimension selection for SPD matrices on Riemannian manifold (DSSR).
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In this paper, we specifically focus on feature extraction, feature selection, and classification strategies based on MI-EEG data.