Add to ORKGThe purpose of this paper is to report on recent approaches to reconstruction problems based on analog, or in other words, infinite-dimensional, image and signal models. We describe three main contributions to this problem. First, linear reconstructions from sampled measurements via so-called generalized sampling (GS). Second, the extension of generalized sampling to inverse and ill-posed problems. And third, the combinatio
Conventional approach in acquisition and reconstruction of images from frequency domain strictly fol...
Shannon’s sampling theory and its variants provide effective solutions to the problem of reconstruct...
AbstractWe show that measures with finite support on the real line are the unique solution to an alg...
The purpose of this paper is to report on recent approaches to reconstruction problems based on anal...
Generalized sampling provides a general mechanism for recovering an unknown input function f(x) # H...
An attractive formulation of the sampling problem is based on the principle of a consistent signal r...
Sampling theory is concerned with the problem of reconstructing a signal f in a Hilbert space from ...
We give a new, very general, formulation of the compressed sensing problem in terms of coordinate pr...
Infinite-dimensional compressed sensing deals with the recovery of analog signals (functions) from l...
A traditional sampling method is that the signal should be sampled at a rate exceeding twice the hig...
Abstract—We consider the problem of the reconstruction of a continuous-time function from the sample...
This paper studies the problem of reconstructing continuous-time signals from discrete-time uniforml...
An attractive formulation of the sampling problem is based on the principle of a consistent signal r...
A spatially distributed system for signal sampling and reconstruction consists of huge amounts of sm...
Compressed sensing is a novel research area, which was introduced in 2006, and since then has alread...
Conventional approach in acquisition and reconstruction of images from frequency domain strictly fol...
Shannon’s sampling theory and its variants provide effective solutions to the problem of reconstruct...
AbstractWe show that measures with finite support on the real line are the unique solution to an alg...
The purpose of this paper is to report on recent approaches to reconstruction problems based on anal...
Generalized sampling provides a general mechanism for recovering an unknown input function f(x) # H...
An attractive formulation of the sampling problem is based on the principle of a consistent signal r...
Sampling theory is concerned with the problem of reconstructing a signal f in a Hilbert space from ...
We give a new, very general, formulation of the compressed sensing problem in terms of coordinate pr...
Infinite-dimensional compressed sensing deals with the recovery of analog signals (functions) from l...
A traditional sampling method is that the signal should be sampled at a rate exceeding twice the hig...
Abstract—We consider the problem of the reconstruction of a continuous-time function from the sample...
This paper studies the problem of reconstructing continuous-time signals from discrete-time uniforml...
An attractive formulation of the sampling problem is based on the principle of a consistent signal r...
A spatially distributed system for signal sampling and reconstruction consists of huge amounts of sm...
Compressed sensing is a novel research area, which was introduced in 2006, and since then has alread...
Conventional approach in acquisition and reconstruction of images from frequency domain strictly fol...
Shannon’s sampling theory and its variants provide effective solutions to the problem of reconstruct...
AbstractWe show that measures with finite support on the real line are the unique solution to an alg...