A unified view of the area of sparse signal processing is presented in tutorial form by
bringing together various fields in which the property of sparsity has been successfully …

The problem of reliably reconstructing a function of sources over a multiple-access channel
(MAC) is considered. It is shown that there is no source–channel separation theorem even …

Agricultural land degradation is a global problem that severely hampers the production of
food needed to sustain the growing world population. Map** of soil degradation by remote …

This article describes a very different approach to the decentralized compression of
networked data. Considering a particularly salient aspect of this struggle that revolves …

Recent results show that a relatively small number of random projections of a signal can
contain most of its salient information. It follows that if a signal is compressible in some …

Compressive Sampling is an emerging theory that is based on the fact that a relatively small
number of random projections of a signal can contain most of its salient information. In this …

Distributed estimation based on measurements from multiple wireless sensors is
investigated. It is assumed that a group of sensors observe the same quantity in …

We consider the distributed estimation of an unknown vector signal in a resource
constrained sensor network with a fusion center. Due to power and bandwidth limitations …

Inspired by the theory of compressed sensing and employing random channel access, we
propose a distributed energy-efficient sensor network scheme denoted by Random Access …

In this paper, we introduce the concept of smoothness for signals supported on the vertices
of a graph. We provide theoretical explanations when and why the Laplacian eigenbasis …