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The Adomian Decomposition Method (ADM) is a very effective approach for solving broad classes of nonlinear partial and ordinary differential equations, with important applications in different fields of applied mathematics, engineering,…

Instrumentation and Methods for Astrophysics · Physics 2021-02-23 Man Kwong Mak , Chun Sing Leung , Tiberiu Harko

Analysing two-dimensional shallow water equations with idealised bottom topographies have many applications in the atmospheric and oceanic sciences; however, restrictive flow pattern assumptions have been made to achieve explicit solutions.…

Fluid Dynamics · Physics 2023-05-01 Chang Liu , Antwan D. Clark

The Adomian decomposition method is a semi-analytical method for solving ordinary and partial nonlinear differential equations. The aim of this paper is to apply Adomian decomposition method to obtain approximate solutions of nonlinear…

Numerical Analysis · Mathematics 2017-12-27 Iqra Javed , Ashfaq Ahmad , Muzammil Hussain , S. Iqbal

Far as we know there are not exact solutions to the equation of motion for a relativistic harmonic oscillator. In this paper, the relativistic harmonic oscillator equation which is a nonlinear ordinary differential equation is studied by…

Classical Analysis and ODEs · Mathematics 2016-10-25 O. González-Gaxiola , J. A. Santiago , J. Ruiz de Chávez

The Alternating Direction Method of Multipliers (ADMM) provides a natural way of solving inverse problems with multiple partial differential equations (PDE) forward models and nonsmooth regularization. ADMM allows splitting these…

Numerical Analysis · Mathematics 2021-04-29 Luke Lozenski , Umberto Villa

Recently, there has been great interest in connections between continuous-time dynamical systems and optimization methods, notably in the context of accelerated methods for smooth and unconstrained problems. In this paper we extend this…

Optimization and Control · Mathematics 2023-01-25 Guilherme França , Daniel P. Robinson , René Vidal

I discuss a recent application of homotopy perturbation and Adomian decomposition methods to the linear and nonlinear Schr\"odinger equations. I propose a generalization of the procedure for the treatment of a wider class of problems.

Mathematical Physics · Physics 2008-08-12 Francisco M. Fernández

Successful application of Adomian decomposition method (ADM) in solving problems in nonlinear ordinary and partial differential equations depend strictly on the Adomian polynomial. In this paper, we present a simple modified known Adomian…

General Mathematics · Mathematics 2020-07-15 E. U. Agom , F. O. Ogunfiditimi

In this work we apply the Adomian decomposition method combined with the Laplace transform (LADM) in order to solve the 1-dimensional nonlinear Schrodinger equation whose nonlinear term presents a nonlinear defocusing strength that varies…

Computational Physics · Physics 2018-01-04 O. Gonzalez-Gaxiola , Pedro Franco , R. Bernal-Jaquez

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

Adomian decomposition method is used for solving the seventh order boundary value problems. The approximate solutions of the problems are calculated in the form of a rapid convergent series and not at grid points. Two numerical examples…

Numerical Analysis · Mathematics 2013-01-17 Shahid S. Siddiqi , Muzammal Iftikhar

We propose conformable Adomian decomposition method (CADM) for fractional partial differential equations (FPDEs). This method is a new Adomian decomposition method (ADM) based on conformable derivative operator (CDO) to solve FPDEs. At the…

General Mathematics · Mathematics 2017-04-11 Omer Acan , Dumitru Baleanu

Alternating Direction Method of Multipliers (ADMM) has been used successfully in many conventional machine learning applications and is considered to be a useful alternative to Stochastic Gradient Descent (SGD) as a deep learning optimizer.…

Optimization and Control · Mathematics 2021-07-07 Junxiang Wang , Fuxun Yu , Xiang Chen , Liang Zhao

We propose a new method for computing Dynamic Mode Decomposition (DMD) evolution matrices, which we use to analyze dynamical systems. Unlike the majority of existing methods, our approach is based on a variational formulation consisting of…

Numerical Analysis · Mathematics 2019-05-24 Omri Azencot , Wotao Yin , Andrea Bertozzi

Originally introduced in the fluid mechanics community, dynamic mode decomposition (DMD) has emerged as a powerful tool for analyzing the dynamics of nonlinear systems. However, existing DMD theory deals primarily with sequential time…

Numerical Analysis · Mathematics 2014-12-17 Jonathan H. Tu , Clarence W. Rowley , Dirk M. Luchtenburg , Steven L. Brunton , J. Nathan Kutz

In the fields of statistics, machine learning, image science, and related areas, there is an increasing demand for decentralized collection or storage of large-scale datasets, as well as distributed solution methods. To tackle this…

Optimization and Control · Mathematics 2024-01-17 Bowen Li , Bin Shi

We develop and modify the Adomian decomposition method (ADecM) to work for a new type of nonlinear matrix differential equations (MDE's) which arise in general relativity (GR) and possibly in other applications. The approach consists in…

General Relativity and Quantum Cosmology · Physics 2010-04-14 Mustapha Azreg-Aïnou

The classic Alternating Direction Method of Multipliers (ADMM) is a popular framework to solve linear-equality constrained problems. In this paper, we extend the ADMM naturally to nonlinear equality-constrained problems, called neADMM. The…

Optimization and Control · Mathematics 2021-03-17 Junxiang Wang , Liang Zhao

Nonlinear effects on the early stage of phase ordering are studied using Adomian's decomposition method for the Ginzburg-Landau equation for a nonconserved order parameter. While the long-time regime and the linear behavior at short times…

Statistical Mechanics · Physics 2009-11-11 M. I. M. Copetti , G. Krein , J. M. Machado , R. S. Marques de Carvalho

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
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