Functional MRI (fMRI) has been widely accepted as a standard tool to study the function of brain. However, because of the limited temporal resolution of MR scanning, researchers h...
We attempt to quantify the possible gains that can be achieved by examining a rate-distortion competition between a conventional and a compressive sampling solution to data rate r...
Leading compressed sensing (CS) methods require m = O (k log(n)) compressive samples to perfectly reconstruct a k-sparse signal x of size n using random projection matrices (e.g., ...
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
In this paper we introduce an information theoretic approach and use techniques from the theory of Huffman codes to construct a sequence of binary sampling vectors to determine a s...