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Inexact alternating direction multiplier methods (ADMMs) are developed for solving general separable convex optimization problems with a linear constraint and with an objective that is the sum of smooth and nonsmooth terms. The approach…

Optimization and Control · Mathematics 2016-04-12 William W. Hager , Hongchao Zhang

Multilinear systems of equations arise in various applications, such as numerical partial differential equations, data mining, and tensor complementarity problems. In this paper, we propose a homotopy method for finding the unique positive…

Numerical Analysis · Mathematics 2017-01-27 Lixing Han

This paper analyzes the convergence of fixed-point iterations of the form u = f(u) and the properties of the inverse of the related pentadiagonal matrices, associated with the fourth-order nonlinear beam equation. This nonlinear problem is…

Numerical Analysis · Mathematics 2021-04-07 Bakytzhan Kurmanbek , Yogi Erlangga , Yerlan Amanbek

In this paper, we introduce a novel approach called the Iterative Aboodh Transform Method (IATM) which utilizes Daftardar--Jafari polynomials for solving non-linear problems. Such method is employed to derive solutions for non-linear…

Numerical Analysis · Mathematics 2025-02-18 Qasim Khan , Anthony Suen

In this paper we propose an iterative method using alternating direction method of multipliers (ADMM) strategy to solve linear inverse problems in Hilbert spaces with general convex penalty term. When the data is given exactly, we give a…

Numerical Analysis · Mathematics 2016-01-13 Yuling Jiao , Qinian Jin , Xiliang Lu , Weijie Wang

We present MADAM, a parallel semidefinite based exact solver for Max-Cut, a problem of finding the cut with maximum weight in a given graph. The algorithm uses branch and bound paradigm that applies alternating direction method of…

Optimization and Control · Mathematics 2021-04-26 Timotej Hrga , Janez Povh

Performing analog computations with metastructures is an emerging wave-based paradigm for solving mathematical problems. For such devices, one major challenge is their reconfigurability, especially without the need for a priori mathematical…

Applied Physics · Physics 2022-06-07 Dimitrios Tzarouchis , Mario Junior Mencagli , Brian Edwards , Nader Engheta

This work is concerned with a direct sampling method (DSM) for inverse acoustic scattering problems using far-field data. The method characterizes some unknown obstacles, inhomogeneous media or cracks, directly through an indicator function…

Mathematical Physics · Physics 2012-12-27 Jingzhi Li , Jun Zou

Various applications such as MRI, solution of PDEs, etc. need to perform an inverse nonequispaced fast Fourier transform (NFFT), i. e., compute $M$ Fourier coefficients from given $N$ nonequispaced data. In the present paper we consider…

Numerical Analysis · Mathematics 2025-06-09 Melanie Kircheis , Daniel Potts

A novel approach for solving linear estimation problem in multi-user massive MIMO systems is proposed. In this approach, the difficulty of matrix inversion is attributed to the incomplete definition of the dot product. The general…

Systems and Control · Computer Science 2015-04-29 Muhammad Ali Raza Anjum

The Homotopy Analysis Method (HAM) is a widely used analytical approach for solving nonlinear problems, yet its theoretical foundation lacks rigorous justification, and its intrinsic correlation with perturbation theory remains ambiguous,…

General Mathematics · Mathematics 2026-04-16 Hang Xu

Non-self-adjoint second-order ordinary differential operators on a finite interval with complex weights are studied. Properties of spectral characteristics are established and the inverse problem of recovering operators from their spectral…

Spectral Theory · Mathematics 2024-02-09 V. A. Yurko

The standard methodology handling nonlinear PDE's involves the two steps: numerical discretization to get a set of nonlinear algebraic equations, and then the application of the Newton iterative linearization or its variants to solve the…

Numerical Analysis · Mathematics 2025-10-20 W. Chen

The alternating direction method of multipliers (ADMM) has recently sparked interest as a flexible and efficient optimization tool for imaging inverse problems, namely deconvolution and reconstruction under non-smooth convex regularization.…

Optimization and Control · Mathematics 2015-06-11 Mariana S. C. Almeida , Mário A. T. Figueiredo

Homotopy analysis method (HAM) was proposed by Liao in 1992 in his PhD thesis for non-linear problems and was applied it in many different problems of mathematical-physics and engineering. In this note, a new development of homotopy…

Numerical Analysis · Mathematics 2021-11-30 Z. K. Eshkuvatov

An efficient procedure using a novel semi-analytical forward solver for identifying heterogeneous and anisotropic elastic parameters from only one full-field measurement is proposed and explored. We formulate the inverse problem as an…

Numerical Analysis · Mathematics 2025-06-19 Xiaopeng Zhu , Zhongyi Huang

Nonlinear ordinary differential equations can rarely be solved analytically. Koopman operator theory provides a way to solve nonlinear systems by mapping nonlinear dynamics to a linear space using eigenfunctions. Unfortunately, finding such…

Dynamical Systems · Mathematics 2022-08-19 Megan Morrison , J. Nathan Kutz

A hybrid analytical method for solving linear and nonlinear fractional partial differential equations is presented. The proposed analytical method is an elegant combination of the Natural Transform Method (NTM) and a well-known method,…

General Mathematics · Mathematics 2018-04-17 Shehu Maitama

We introduce a new overlapping Domain Decomposition Method (DDM) to solve the fully nonlinear Monge-Amp\`ere equation. While DDMs have been extensively studied for linear problems, their application to fully nonlinear partial differential…

Numerical Analysis · Mathematics 2023-06-05 Yassine Boubendir , Jake Brusca , Brittany Froese Hamfeldt , Tadanaga Takahashi

In this paper, we consider a deep learning approach to the limited aperture inverse obstacle scattering problem. It is well known that traditional deep learning relies solely on data, which may limit its performance for the inverse problem…

Numerical Analysis · Mathematics 2024-11-05 Yunwen Yin , Liang Yan