3 papers
cs.DS2016
Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations
Yoann Isaac, Quentin Barthélemy, Cédric Gouy-Pailler +2
This paper addresses the structurally-constrained sparse decomposition of multi-dimensional signals onto overcomplete families of vectors, called dictionaries. The contribution of…
cs.LG2013
Multivariate Temporal Dictionary Learning for EEG
Quentin Barthélemy, Cédric Gouy-Pailler, Yoann Isaac +3
This article addresses the issue of representing electroencephalographic (EEG) signals in an efficient way. While classical approaches use a fixed Gabor dictionary to analyze EEG s…
cs.DS2013
Multi-dimensional sparse structured signal approximation using split Bregman iterations
Yoann Isaac, Quentin Barthélemy, Jamal Atif +2
The paper focuses on the sparse approximation of signals using overcomplete representations, such that it preserves the (prior) structure of multi-dimensional signals. The underlyi…