In this paper, motivated by network inference and tomography applications, we study the problem of compressive sensing for sparse signal vectors over graphs. In particular, we are ...
Sparse coding networks, which utilize unsupervised learning to maximize coding efficiency, have successfully reproduced response properties found in primary visual cortex [1]. Ho...
William K. Coulter, Cristopher J. Hillar, Guy Isle...
In this work, we propose algorithms to recursively and causally reconstruct a sequence of natural images from a reduced number of linear projection measurements taken in a domain ...
3D MRI of the upper airway has provided valuable insights into vocal tract shaping and data for the modeling of speech production. Small movements of articulators can lead to larg...
Yoon-Chul Kim, Shrikanth S. Narayanan, Krishna S. ...
Recently, significant attention in compressed sensing has been focused on Basis Pursuit, exchanging the cardinality operator with the l1-norm, which leads to a linear formulation...
Christian R. Berger, Javier Areta, Krishna R. Patt...