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Motivated by nonconvex, inconsistent feasibility problems in imaging, the relaxed alternating averaged reflections algorithm, or relaxed Douglas-Rachford algorithm (DR$\lambda$), was first proposed over a decade ago. Convergence results for…

Optimization and Control · Mathematics 2020-03-26 D. Russell Luke , Anna-Lena Martins

We consider the Modified Craig-Sneyd (MCS) scheme which forms a prominent time stepping method of the Alternating Direction Implicit type for multidimensional time-dependent convection-diffusion equations with mixed spatial derivative…

Numerical Analysis · Mathematics 2014-12-08 Karel in 't Hout , Maarten Wyns

Rough surface scattering problems are always very challenging both theoretically and numerically. In this paper, we adopt the Bloch transform and the perturbation theory to investigate a special case, i.e., when the rough surface is a…

Analysis of PDEs · Mathematics 2018-12-04 Ruming Zhang

In this article, we consider the numerical approximation of far-field statistics for acoustic scattering problems in the case of random obstacles. In particular, we consider the computation of the expected far-field pattern and the expected…

Numerical Analysis · Mathematics 2018-10-09 Helmut Harbrecht , Nikola Ilić , Michael D. Multerer

Practical applications of microwave imaging often require the solution of inverse scattering problems with inhomogeneous backgrounds. Towards this end, a novel inversion strategy, which combines the multi-scaling (MS) regularization scheme…

Signal Processing · Electrical Eng. & Systems 2024-01-08 Yu Zhong , Francesco Zardi , Marco Salucci , Giacomo Oliveri , Andrea Massa

The contrast source inversion (CSI) method and the subspace-based optimization method (SOM) are first proposed in 1997 and 2009, respectively, and subsequently modified. The two methods and their variants share several properties and thus…

Numerical Analysis · Mathematics 2026-03-25 Qiao Hu , Bo Zhang , Haiwen Zhang

This paper presents a new method, based on the well-known method of moments (MoM), for the numerical electromagnetic analysis of scattering and radiation from metallic or dielectric structures, or both structure types in the same…

Anomaly detection in random fields is an important problem in many applications including the detection of cancerous cells in medicine, obstacles in autonomous driving and cracks in the construction material of buildings. Such anomalies are…

Statistics Theory · Mathematics 2023-11-17 Claudia Kirch , Philipp Klein , Marco Meyer

Metasurfaces enable powerful control of electromagnetic waves using subwavelength planar structures, but their deeply subwavelength periodicity typically suppresses propagating diffraction orders, which limits the number of available…

Optics · Physics 2026-05-14 Karim Achouri

We consider the inverse obstacle scattering problem of determining both the shape and the "equivalent impedance" from far field measurements at a fixed frequency. In this work, the surface impedance is represented by a second order surface…

Numerical Analysis · Mathematics 2013-07-24 Laurent Bourgeois , Nicolas Chaulet , Houssem Haddar

We propose a new approach to linear ill-posed inverse problems. Our algorithm alternates between enforcing two constraints: the measurements and the statistical correlation structure in some transformed space. We use a non-linear multiscale…

Computational Engineering, Finance, and Science · Computer Science 2018-12-04 Ivan Dokmanić , Joan Bruna , Stéphane Mallat , Maarten de Hoop

We introduce an integral representation of the Monge-Amp\`ere equation, which leads to a new finite difference method based upon numerical quadrature. The resulting scheme is monotone and fits immediately into existing convergence proofs…

Numerical Analysis · Mathematics 2022-12-01 Jake Brusca , Brittany Froese Hamfeldt

This paper investigates the inverse scattering problem of recovering a sound-soft obstacle using passive measurements taken from randomly distributed point sources. The randomness introduced by these sources poses significant challenges,…

Numerical Analysis · Mathematics 2024-07-08 Yunwen Yin , Liang Yan

We propose a correction to the conventional Rytov approximation (RA) and investigate its performance for predicting wave scattering under strong scattering conditions. An important motivation for the correction and investigation is to help…

Computational Physics · Physics 2022-11-30 Amartansh Dubey , Xudong Chen , Ross Murch

We introduce a numerical variational method based on the Rayleigh-Ritz optimization principle for predicting two-dimensional self-trapped beams in nonlinear media. This technique overcomes the limitation of the traditional variational…

Optics · Physics 2018-04-04 Erick I. Duque , Servando Lopez-Aguayo , Boris A. Malomed

Multiple scattering methods are widely used to reduce the computational complexity of acoustic or electromagnetic scattering problems when waves propagate through media containing many identical inclusions. Historically, this numerical…

Numerical Analysis · Mathematics 2024-08-07 Carlos Borges , Leslie Greengard , Michael O'Neil , Manas Rachh

The representation of small scale barriers, such as sea-walls, in coastal flooding simulations is a common computational constraint that can be difficult to overcome due to the combination of the need for resolution and the CFL constraining…

Numerical Analysis · Mathematics 2021-12-21 Chanyang Ryoo , Kyle Mandli

In recent years, a distributed Douglas-Rachford splitting method (DDRSM) has been proposed to tackle multi-block separable convex optimization problems. This algorithm offers relatively easier subproblems and greater efficiency for…

Optimization and Control · Mathematics 2024-11-19 Leyu Hu , Jiaxin Xie , Xingju Cai , Deren Han

An innovative 3-D radar imaging technique is developed for fast and efficient identification and characterization of radar backscattering components of complex objects, when the collected scattered field is made of polarization-diverse…

Information Theory · Computer Science 2015-06-25 Pierre Minvielle , Pierre Massaloux , Jean-François Giovannelli

Mirror Descent (MD) is a scalable first-order method widely used in large-scale optimization, with applications in image processing, policy optimization, and neural network training. This paper generalizes MD to optimization on Riemannian…

Machine Learning · Statistics 2026-03-19 Jiaxin Jiang , Lei Shi , Jiyuan Tan