There are two main classes of decoding algorithms for "compressed sensing," those which run time time polynomial in the signal length and those which use sublinear resou...
Abstract--In this paper, we present a concise and coherent analysis of the constrained `1 minimization method for stable recovering of high-dimensional sparse signals both in the n...
Standard compressive sensing results state that to exactly recover an s sparse signal in Rp , one requires O(s · log p) measurements. While this bound is extremely useful in prac...
Abstract--This paper develops an optimal decentralized algorithm for sparse signal recovery and demonstrates its application in monitoring localized phenomena using energy-constrai...
This paper presents a novel time-adaptive estimation technique by revisiting the classical Wiener-Hopf equation. Any convex and not necessarily differentiable function can be used...