The need of reconstructing discrete-valued sparse signals from few measurements, that is
solving an underdetermined system of linear equations, appears frequently in science and …

An enhanced algorithm for the reconstruction of discrete‐valued sparse vectors from an
underdetermined system of linear equations under the presence of noise is presented …

In Compressed Sensing, a real-valued sparse vector has to be reconstructed from an
underdetermined system of linear equations. However, in many applications of digital …

In sensor networks, many sensors with very low duty cycles transmit their discrete-valued
data independently to a fusion center. This central instance has to estimate the individual …

Iterative algorithms for the reconstruction in compressed sensing are studied. In particular,
message passing approaches are reviewed and it is discussed how the underlying problem …

In Compressed Sensing, a real-valued sparse vector has to be estimated from an
underdetermined system of linear equations. In many applications, however, the elements of …

In the multiple-input/multiple-output scenario which is an important field of research in
communications engineering, the data transmission from a couple of transmit antennas to a …

In classical Compressed Sensing, real-valued sparse vectors have to be estimated from an
underdetermined system of linear equations. However, in many applications such as sensor …

In Compressed Sensing, a real-valued sparse vector has to be recovered from an
underdetermined system of linear equations. In many applications, however, the elements of …

The need of reconstructing discrete-valued sparse signals from few measurements, that is
solving an undetermined system of linear equations, appears frequently in science and …