Riemannian geometry-based classification (RGBC) gained popularity in the field of brain-computer interfaces (BCIs) lately, due to its ability to deal with non-stationarities arising in ...

To address this issue, we propose a novel CL framework, the Riemannian-Euclidean Contrastive Learning Network (RECLNet). The proposed RECLNet allows direct input of polarimetric covariance matrices, ...

Then, we consider the robust precoder design aiming to maximize the upper bound of the ergodic weighted sum-rate (WSR) on the Riemannian submanifold formed by the precoders satisfying the total power ...

Nature Research Intelligence Topics enable transformational understanding and discovery in research by categorising any document into meaningful, accessible topics. Read this blog to understand ...

The algorithm is founded on three assumptions about the data: The data is uniformly distributed on a Riemannian manifold; The Riemannian metric is locally constant (or can be approximated as such); ...