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...
—We consider a multi-static radar scenario with spatially dislocated receivers that can individually extract delay information only. Furthermore, we assume that the receivers are...
High resolution through-the-wall radar imaging (TTWRI) demands wideband signals and large array apertures. Thus a vast amount of measurements is needed for a detailed reconstructi...
Michael Leigsnering, Christian Debes, Abdelhak M. ...
In this paper, a new approach for Confocal Microscopy (CM) based on the framework of compressive sensing is developed. In the proposed approach, a point illumination and a random ...
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x RN that are of high dimension N but are constrained to reside in a low-dimen...
Minhua Chen, Jorge Silva, John William Paisley, Ch...