An overview of the recent advancements in the development of microwave imaging
procedures based on the exploitation of the regularization theory in Lebesgue spaces is …

The linearity of the scattering phenomenon with respect to primary sources allows to
recombine a posteriori the available experiments and build, in a synthetic fashion, new …

An innovative nonlinear inverse scattering approach in variable exponent Lebesgue spaces
is proposed for microwave imaging purposes. The main objective of the approach is to …

In this article, we present a new diagnostic technique for printed circuit boards (PCBs) and
integrated circuits (ICs). This technique consists of an array-probe scanning system and the …

This paper describes a U-net based Deep Learning (DL) approach in combination with
Subspace-Based Variational Born Iterative Method (SVBIM) to provide a solution for the …

Recovering low-rank and sparse components from missing observations is an essential
problem in various fields. In this paper, we have proposed a method to address the missing …

Direction of arrival (DOA) estimation is an essential task in the array signal processing. In
this study, the authors attempt to address the off‐grid issue for the two‐dimensional (2D) …

This paper considers the deep-learning-aided compressed video sensing problem. To this
end, a deep generative adversarial network has been proposed to provide an approximation …

In this paper, we present a novel approach for the reconstruction of sparse graph signals
using a distributed adaptive thresholding recursive least squares algorithm. Our proposed …

Direction of arrival (DOA) estimation has paramount importance in array signal processing
tasks. A practical issue regarding DOA estimation is the uncertainty in gain/phase of some of …