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Von Neumann stability analysis, a well-known Fourier-based method, is a widely used technique for assessing stability in numerical computations. However, as noted in "Numerical Solution of Partial Differential Equations: Finite Difference…

Numerical Analysis · Mathematics 2023-10-13 Arun Govind Neelan

A parametric constrained convex optimal control problem, where the initial state is perturbed and the linear state equation contains a noise, is considered in this paper. Formulas for computing the subdifferential and the singular…

Optimization and Control · Mathematics 2017-07-14 Duong Thi Viet An , Jen-Chih Yao , Nguyen Dong Yen

A nonlinear partial differential equation is a nonlinear relationship between an unknown function and how it changes due to two or more input variables. A numerical method reduces such an equation to arithmetic for quick visualization, but…

History and Overview · Mathematics 2019-09-27 R. Corban Harwood

In this paper, we study the qualitative behaviour of approximation schemes for Backward Stochastic Differential Equations (BSDEs) by introducing a new notion of numerical stability. For the Euler scheme, we provide sufficient conditions in…

Probability · Mathematics 2014-07-04 Jean-François Chassagneux , Adrien Richou

Based on a regularized Volterra equation, two different approaches for numerical differentiation are considered. The first approach consists of solving a regularized Volterra equation while the second approach is based on solving a…

Numerical Analysis · Mathematics 2007-12-02 N. S. Hoang , A. G. Ramm

To predict allowable time-step size for the fully discretized nonlinear differential equations, a stability theory is developed using exact determination of an infinite perturbation series. Mathematical induction is used to determine the…

Numerical Analysis · Mathematics 2013-11-05 Arash Ghasemi , Kidambi Sreenivas , Lafayette K. Taylor

Several algorithms in computer algebra involve the computation of a power series solution of a given ordinary differential equation. Over finite fields, the problem is often lifted in an approximate $p$-adic setting to be well-posed. This…

Symbolic Computation · Computer Science 2023-06-12 Pierre Lairez , Tristan Vaccon

Probabilistic solvers for ordinary differential equations (ODEs) provide efficient quantification of numerical uncertainty associated with simulation of dynamical systems. Their convergence rates have been established by a growing body of…

Machine Learning · Statistics 2020-12-21 Nicholas Krämer , Philipp Hennig

We study approximation of non-autonomous linear differential equations with variable delay over infinite intervals. We use piecewise constant argument to obtain a corresponding discrete difference equation. The study of numerical…

Classical Analysis and ODEs · Mathematics 2016-07-26 Daniel Sepúlveda

Numerical methods for the Euler equations with a singular source are discussed in this paper. The stationary discontinuity induced by the singular source and its coupling with the convection of fluid presents challenges to numerical…

Numerical Analysis · Mathematics 2022-03-14 Changsheng Yu , Tiegang Liu , Chengliang Feng

In this work, we systematically investigate linear multi-step methods for differential equations with memory. In particular, we focus on the numerical stability for multi-step methods. According to this investigation, we give some…

Numerical Analysis · Mathematics 2023-10-30 Guihong Wang , Yuqing Li , Tao Luo , Zheng Ma , Nung Kwan Yip , Guang Lin

A new explicit stochastic scheme of order 1 is proposed for solving commutative stochastic differential equations (SDEs) with non-globally Lipschitz continuous coefficients. The proposed method is a semi-tamed version of Milstein scheme to…

Numerical Analysis · Mathematics 2021-10-13 Yulong Liu , Yuanling Niu , Xiujun Cheng

This paper explores the critical role of differentiation approaches for data-driven differential equation discovery. Accurate derivatives of the input data are essential for reliable algorithmic operation, particularly in real-world…

Machine Learning · Computer Science 2023-11-13 Mikhail Masliaev , Ilya Markov , Alexander Hvatov

This work is concerned with the quantification of the epistemic uncertainties induced the discretization of partial differential equations. Following the paradigm of probabilistic numerics, we quantify this uncertainty probabilistically.…

Probability · Mathematics 2016-07-14 Ilias Bilionis

We develop a randomized Newton's method for solving differential equations, based on a fully connected neural network discretization. In particular, the randomized Newton's method randomly chooses equations from the overdetermined nonlinear…

Numerical Analysis · Mathematics 2019-12-09 Qipin Chen , Wenrui Hao

One method to determine whether or not a system of partial differential equations is consistent is to attempt to construct a solution using merely the "algebraic data" associated to the system. In technical terms, this translates to the…

Commutative Algebra · Mathematics 2017-11-13 Richard Gustavson , Omar León Sánchez

Various types of stabilizing controls lead to a deterministic difference equation with the following property: once the initial value is positive, the solution tends to the unique positive equilibrium. Introducing additive perturbations can…

Dynamical Systems · Mathematics 2016-06-07 Elena Braverman , Alexandra Rodkina

Numerical solving differential equations with fractional derivatives requires elimination of the singularity which is inherent in the standard definition of fractional derivatives. The method of integration by parts to eliminate this…

Numerical Analysis · Mathematics 2022-01-26 Pavel B. Dubovski , Jeffrey A. Slepoi

The numerical methods for differential equation solution allow obtaining a discrete field that converges towards the solution if the method is applied to the correct problem. Nevertheless, the numerical methods have the restricted class of…

Numerical Analysis · Mathematics 2023-07-03 Alexander Hvatov , Tatiana Tikhonova

This article focuses on a nonlinear Neumann boundary feedback control formulation for the viscous Burgers' equation and develops a class of finite difference schemes to achieve global stabilization. The proposed procedure, known as the…

Numerical Analysis · Mathematics 2025-12-02 Shishu Pal Singh , Sudeep Kundu