In previous work we introduced a new missing data imputation method for ASR, dubbed sparse imputation. We showed that the method is capable of maintaining good recognition accurac...
The problem of transmit beamforming for single-group multicasting is considered, where the objective is to transmit common information to a (large) number of users. The transmitte...
Ahmed Abdelkader, Imran Wajid, Alex B. Gershman, N...
— We study the inversion of a random field from pointwise measurements collected by a sensor network. We assume that the field has a sparse representation in a known basis. To ...
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
In this paper, a data-driven extension of the variational algorithm is proposed. Based on a few selected sensors, target tracking is performed distributively without any informati...
Hichem Snoussi, Jean-Yves Tourneret, Petar M. Djur...