RFNet: Riemannian Fusion Network for EEG-based Brain-Computer Interfaces

19 Aug 2020 Guangyi Zhang Ali Etemad

This paper presents the novel Riemannian Fusion Network (RFNet), a deep neural architecture for learning spatial and temporal information from Electroencephalogram (EEG) for a number of different EEG-based Brain Computer Interface (BCI) tasks and applications. The spatial information relies on Spatial Covariance Matrices (SCM) of multi-channel EEG, whose space form a Riemannian Manifold due to the Symmetric and Positive Definite structure... (read more)

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