Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-N...
Dror Baron, Shriram Sarvotham, Richard G. Baraniuk
This paper considers conceptual modelling for three purposes namely data modelling, knowledge modelling and ontology modelling. It differentiates between the nature of the concept...
Tharam S. Dillon, Elizabeth Chang, Maja Hadzic, Po...
—We study target tracking with wireless binary sensor networks, in which each sensor can return only 1-bit information regarding target’s presence or absence in its sending ran...
We propose a supervised word sense disambiguation (WSD) method using tree-structured conditional random fields (TCRFs). By applying TCRFs to a sentence described as a dependency t...
In this paper we model the components of the compressive sensing (CS) problem using the Bayesian framework by utilizing a hierarchical form of the Laplace prior to model sparsity ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...