Revisiting Riemannian geometry-based EEG decoding through approximate joint diagonalization
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/aca4fc
Abstract: Objective. The wider adoption of Riemannian geometry in electroencephalography (EEG) processing is hindered by two factors: (a) it involves the manipulation of complex mathematical formulations and, (b) it leads to computationally demanding tasks. The main… read more here.
Keywords: approximate joint; joint diagonalization; revisiting riemannian; geometry ... See more keywords
Riemannian Optimization and Approximate Joint Diagonalization for Blind Source Separation
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2018.2795539
Abstract: We consider the blind source separation (BSS) problem and the closely related approximate joint diagonalization (AJD) problem of symmetric positive definite (SPD) matrices. These two problems can be reduced to an optimization problem with three… read more here.
Keywords: approximate joint; source separation; riemannian optimization; blind source ... See more keywords