We propose a non-stationary iterated network Tikhonov (iNETT) method for the solution of ill-
posed inverse problems. The iNETT employs deep neural networks to build a data-driven …

The need to solve discrete ill-posed problems arises in many areas of science and
engineering. Solutions of these problems, if they exist, are very sensitive to perturbations in …

Proximal–gradient methods are widely employed tools in imaging that can be accelerated
by adopting variable metrics and/or extrapolation steps. One crucial issue is the inexact …

Discrete ill-posed inverse problems arise in various areas of science and engineering. The
presence of noise in the data often makes it difficult to compute an accurate approximate …

In recent decades, a remarkable amount of research has been carried out regarding fast
solvers for large linear systems resulting from various discretizations of fractional differential …

Bregman-type iterative methods have received considerable attention in recent years due to
their ease of implementation and the high quality of the computed solutions they deliver …

Image deblurring is relevant in many fields of science and engineering. To solve this
problem, many different approaches have been proposed and among the various methods …

We propose an algorithm for solving the basis pursuit problem min u∈ C n {∥ u∥ 1: A u= f}.
Our starting motivation is the algorithm for compressed sensing, proposed by Qiao, Li and …

Linear inverse problems arise in diverse engineering fields especially in signal and image
reconstruction. The development of computational methods for linear inverse problems with …

Wavelet frames have been widely applied in the field of image processing, due to their good
capability for sparsely representing the piece-wise smooth functions which are suitable for …