or each dataset, we present the observation period in terms of the number of days, the minimum and maximum numbers of nodes in the daily partition of the dataset (Nmin and Nmax), and the number of dis
or each dataset, we present the observation period in terms of the number of days, the minimum and maximum numbers of nodes in the daily partition of the dataset (Nmin and Nmax), and the number of dis
In this study, we introduce a novel Field-Agnostic Riemannian-Kernel Alignment (FARKA) method to advance the classification of motion imagination in Brain-Computer Interface (BCI) systems. BCI systems
