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In this paper, we study direct and indirect Galerkin method for solving linear Integral-Algebraic Equations of index 1. Convergence of indirect method is also analyzed.

Numerical Analysis · Mathematics 2012-12-18 B. Shiri

These lecture notes introduce the Galerkin method to approximate solutions to partial differential and integral equations. We begin with some analysis background to introduce this method in a Hilbert Space setting, and subsequently…

Analysis of PDEs · Mathematics 2011-12-07 Raghavendra Venkatraman

We introduce a general framework for approximating parabolic Stochastic Partial Differential Equations (SPDEs) based on fluctuation-dissipation balance. Using this approach we formulate Stochastic Discontinuous Galerkin Methods (SDGM). We…

Numerical Analysis · Mathematics 2023-02-28 Will Pazner , Nathaniel Trask , Paul J. Atzberger

We present a high-order accurate fully discrete numerical scheme for solving Initial Boundary Value Problems (IBVPs) within the Continuous Galerkin (CG)-based Finite Element framework. Both the spatial and time approximation in…

Mathematical Physics · Physics 2026-01-09 Mrityunjoy Mandal , Jan Nordström , Arnaud G Malan

We consider a linear elliptic partial differential equation (PDE) with a generic uniformly bounded parametric coefficient. The solution to this PDE problem is approximated in the framework of stochastic Galerkin finite element methods. We…

Numerical Analysis · Mathematics 2020-06-05 Alex Bespalov , Feng Xu

In this paper, we present a Galerkin method for Abel-type integral equation with a general class of kernel. Stability and quasi-optimal convergence estimates are derived in ractional-order Sobolev norms. The fully-discrete Galerkin method…

Numerical Analysis · Mathematics 2018-03-08 Urs Vögeli , Khadijeh Nedaiasl , Stefan A. Sauter

At present, deep learning based methods are being employed to resolve the computational challenges of high-dimensional partial differential equations (PDEs). But the computation of the high order derivatives of neural networks is costly,…

Numerical Analysis · Mathematics 2021-03-17 Quanhui Zhu , Jiang Yang

We study the problem of identifying unknown processes embedded in time-dependent partial differential equation (PDE) using observational data, with an application to advection-diffusion type PDE. We first conduct theoretical analysis and…

Numerical Analysis · Mathematics 2021-07-13 Zhen Chen , Kailiang Wu , Dongbin Xiu

These lecture notes for a graduate course present an introduction to the mathematical theory of finite element methods for the numerical solution of partial differential equations. Covered are conforming and nonconforming (in particular,…

Numerical Analysis · Mathematics 2021-08-20 Christian Clason

In this work, solvers and preconditioners based on Gauss-Seidel and Jacobi algorithms are explored for stochastic Galerkin discretization of partial differential equations (PDEs) with random input data. Gauss-Seidel and Jacobi algorithms…

Numerical Analysis · Mathematics 2019-04-16 Ramakrishna Tipireddy , Eric T. Phipps , Roger G. Ghanem

We develop a hybrid spatial discretization for the wave equation in second order form, based on high-order accurate finite difference methods and discontinuous Galerkin methods. The hybridization combines computational efficiency of finite…

Numerical Analysis · Mathematics 2022-10-26 Siyang Wang , Gunilla Kreiss

Unique existence of analytically strong solutions to stochastic partial differential equations (SPDE) with drift given by the subdifferential of a quasi-convex function and with general multiplicative noise is proven. The proof applies a…

Probability · Mathematics 2011-04-22 Benjamin Gess

This paper presents a primal-dual weak Galerkin (PD-WG) finite element method for a class of second order elliptic equations of Fokker-Planck type. The method is based on a variational form where all the derivatives are applied to the test…

Numerical Analysis · Mathematics 2017-04-20 Chunmei Wang , Junping Wang

In this paper, we present a new numerical method to solve fractional differential equations. Given a fractional derivative of arbitrary real order, we present an approximation formula for the fractional operator that involves integer-order…

Numerical Analysis · Mathematics 2015-12-16 Ricardo Almeida , Nuno R. O. Bastos

The proximal Galerkin finite element method is a high-order, low-iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of point-wise bound constraints in infinite-dimensional function spaces.…

Numerical Analysis · Mathematics 2024-12-18 Brendan Keith , Thomas M. Surowiec

In the present study, a numerical method, perturbation-iteration algorithm (shortly PIA), have been employed to give approximate solutions of nonlinear fractional-integro differential equations (FIDEs). Comparing with the exact solution,…

Numerical Analysis · Mathematics 2016-07-28 Mehmet Senol , I. T. Dolapci

In this article we obtain an optimal best approximation type result for fully discrete approximations of the transient Stokes problem. For the time discretization we use the discontinuous Galerkin method and for the spatial discretization…

Numerical Analysis · Mathematics 2021-07-26 Niklas Behringer , Dmitriy Leykekhman , Boris Vexler

In this study, we examine numerical approximations for 2nd-order linear-nonlinear differential equations with diverse boundary conditions, followed by the residual corrections of the first approximations. We first obtain numerical results…

Numerical Analysis · Mathematics 2023-06-19 Shovan Sourav Datta Pranta , Md. Shafiqul Islam

This paper develops and analyzes a class of semi-discrete and fully discrete weak Galerkin finite element methods for unsteady incompressible convective Brinkman-Forchheimer equations. For the spatial discretization, the methods adopt the…

Numerical Analysis · Mathematics 2024-10-30 Xiaojuan Wang , Jihong Xiao , Xiaoping Xie , Shiquan Zhang

One popular approach to option pricing in L\'evy models is through solving the related partial integro differential equation (PIDE). For the numerical solution of such equations powerful Galerkin methods have been put forward e.g. by Hilber…

Computational Finance · Quantitative Finance 2016-03-29 Maximilian Gaß , Kathrin Glau