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We present extended Galerkin neural networks (xGNN), a variational framework for approximating general boundary value problems (BVPs) with error control. The main contributions of this work are (1) a rigorous theory guiding the construction…

Numerical Analysis · Mathematics 2024-12-04 Mark Ainsworth , Justin Dong

We present a new method for solving parametrized linear systems. Under certain assumptions on the parametrization, solutions to the linear systems for all parameters can be accurately approximated by linear combinations of solutions to…

Numerical Analysis · Mathematics 2014-06-03 Anil Damle , Lin Lin , Lexing Ying

This work presents an algorithmic scheme for solving the infinite-time constrained linear quadratic regulation problem. We employ an accelerated version of a popular proximal gradient scheme, commonly known as the Forward-Backward Splitting…

Optimization and Control · Mathematics 2015-01-20 Giorgos Stathopoulos , Milan Korda , Colin N. Jones

Contour integral methods for nonlinear eigenvalue problems seek to compute a subset of the spectrum in a bounded region of the complex plane. We briefly survey this class of algorithms, establishing a relationship to system realization…

Numerical Analysis · Mathematics 2021-01-01 Michael C. Brennan , Mark Embree , Serkan Gugercin

We present an indirect higher order boundary element method utilising NURBS mappings for exact geometry representation and an interpolation-based fast multipole method for compression and reduction of computational complexity, to counteract…

Numerical Analysis · Mathematics 2018-02-14 Jürgen Dölz , Helmut Harbrecht , Stefan Kurz , Sebastian Schöps , Felix Wolf

We consider a linear second order parabolic system with a third order dispersion term. This type of system arises when considering a nonlinear model equation describing the motion of a vortex filament with axial flow immersed in an…

Analysis of PDEs · Mathematics 2012-01-04 Masashi Aiki , Tatsuo Iguchi

This article presents a new approach to the real-time solution of inverse problems on embedded systems. The class of problems addressed corresponds to ordinary differential equations (ODEs) with generalized linear constraints, whereby the…

Discrete Mathematics · Computer Science 2014-06-03 Christoph Gugg , Matthew Harker , Paul O'Leary , Gerhard Rath

This work develops a nonlinear multigrid method for diffusion problems discretized by cell-centered finite volume methods on general unstructured grids. The multigrid hierarchy is constructed algebraically using aggregation of degrees of…

Numerical Analysis · Mathematics 2020-10-29 Chak Shing Lee , François Hamon , Nicola Castelletto , Panayot S. Vassilevski , Joshua White

In this paper, we propose an efficient parallelization strategy for boundary element method (BEM) solvers that perform the electromagnetic analysis of structures with lossy conductors. The proposed solver is accelerated with the adaptive…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-11-30 Damian Marek , Shashwat Sharma , Piero Triverio

For the first time, some hypersingular nonlinear boundary-value problems with a small parameter~$\varepsilon$ at the highest derivative are described. These problems essentially (qualitatively and quantitatively) differ from the usual…

Analysis of PDEs · Mathematics 2018-02-14 Andrei D. Polyanin , Inna K. Shingareva

The objective of this study is to present a novel, efficient, and fast direct method for solving linear systems of equations whose coefficient matrix is a tridiagonal Quasi-Toeplitz matrix. Such matrices are frequently encountered in the…

Numerical Analysis · Mathematics 2024-12-24 Shahin Hasanbeigi

This paper is concerned with a novel deep learning method for variational problems with essential boundary conditions. To this end, we first reformulate the original problem into a minimax problem corresponding to a feasible augmented…

Numerical Analysis · Mathematics 2022-05-10 Jianguo Huang , Haoqin Wang , Tao Zhou

In this paper we propose a method to generate suitably refined finite element meshes using neural networks. As a model problem we consider a linear elasticity problem on a planar domain (possibly with holes) having a polygonal boundary. We…

Numerical Analysis · Mathematics 2022-03-16 Chiu Ling Chan , Felix Scholz , Thomas Takacs

This paper is concerned with recovering the solution of a final value problem associated with a parabolic equation involving a non linear source and a non-local term, which to the best of our knowledge has not been studied earlier. It is…

Numerical Analysis · Mathematics 2023-12-20 Subhankar Mondal

The finite element method is used to approximately solve boundary value problems for differential equations. The method discretises the parameter space and finds an approximate solution by solving a large system of linear equations. Here we…

Quantum Physics · Physics 2016-03-23 Ashley Montanaro , Sam Pallister

A system of linear equations is normally understood as a linear mapping between two vector spaces. However, most direct solutions (e.g., QR, LU, ...) rely on the inelegant approach of back-substitution: a significant departure from such a…

Rings and Algebras · Mathematics 2020-10-05 Michael F. Zimmer

We present a stationary iteration method, namely Alternating Symmetric positive definite and Scaled symmetric positive semidefinite Splitting (ASSS), for solving the system of linear equations obtained by using finite element discretization…

Numerical Analysis · Mathematics 2021-09-06 Davod Khojasteh Salkuyeh

Motivated by the existing complications of finding solutions of Eringen nonlocal model, an alternative model is developed here. The new formulation of the nonlocal elasticity is centered upon expressing the dynamic equilibrium requirements…

Applied Physics · Physics 2018-10-11 Mohamed Shaat

This paper considers the finite element solution of the boundary value problem of Poisson's equation and proposes a guaranteed em a posteriori local error estimation based on the hypercircle method. Compared to the existing literature on…

Numerical Analysis · Mathematics 2021-12-17 Taiga Nakano , Xuefeng Liu

We propose a neural network-based algorithm for solving forward and inverse problems for partial differential equations in unsupervised fashion. The solution is approximated by a deep neural network which is the minimizer of a cost…

Machine Learning · Computer Science 2019-04-12 Leah Bar , Nir Sochen