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The paper concerns a class of $n$-dimensional non-autonomous delay differential equations obtained by adding a non-monotone delayed perturbation to a linear homogeneous cooperative system of ordinary differential equations. This family…

Classical Analysis and ODEs · Mathematics 2018-07-10 Teresa Faria , Rafael Obaya , Ana M. Sanz

This paper is part of a series of papers in which the asymptotic theory and appropriate symbolic computer code are developed to compute the asymptotic expansion of the solution of an n-th order ordinary differential equation. The paper…

Spectral Theory · Mathematics 2025-10-20 B. M. Brown , M. S. P. Eastham , D. K. R. McCormack

A method of representation of a solution as segments of the series in powers of the step of the independent variable is expanded for solving complex systems of ordinary differential equations (ODE): the Lorenz system and other systems. A…

Numerical Analysis · Computer Science 2014-05-26 Vladimir Aristov , Andrey Stroganov

The purpose of this paper is to propose a semi-analytical technique convenient for numerical approximation of solutions of the initial value problem for $p$-dimensional delayed and neutral differential systems with constant, proportional…

Classical Analysis and ODEs · Mathematics 2019-01-29 Josef Rebenda , Zdeněk Šmarda

The solution of systems of non-autonomous linear ordinary differential equations is crucial in a variety of applications, such us nuclear magnetic resonance spectroscopy. A new method with spectral accuracy has been recently introduced in…

Numerical Analysis · Mathematics 2022-10-14 Stefano Pozza , Niel Van Buggenhout

In this paper, we propose two novel fourth-order integrators that exhibit uniformly high accuracy and long-term near conservations for solving the nonlinear Dirac equation (NLDE) in the nonrelativistic regime. In this regime, the solution…

Numerical Analysis · Mathematics 2025-03-21 Lina Wang , Bin Wang , Jiyong Li

Neural ordinary differential equations (NODEs) -- parametrizations of differential equations using neural networks -- have shown tremendous promise in learning models of unknown continuous-time dynamical systems from data. However, every…

Machine Learning · Computer Science 2023-01-02 Franck Djeumou , Cyrus Neary , Eric Goubault , Sylvie Putot , Ufuk Topcu

In this paper, we investigate the fixed-time behavioral control problem for a team of second-order nonlinear agents, aiming to achieve a desired formation with collision/obstacle~avoidance. In the proposed approach, the two behaviors(tasks)…

Optimization and Control · Mathematics 2021-03-12 Ning Zhou , Xiaodong Cheng , Zhongqi Sun , Yuanqing Xia

We prove the optimal strong convergence rate of a fully discrete scheme, based on a splitting approach, for a stochastic nonlinear Schr\"odinger (NLS) equation. The main novelty of our method lies on the uniform a priori estimate and…

Numerical Analysis · Mathematics 2019-02-25 Jianbo Cui , Jialin Hong , Zhihui Liu , Weien Zhou

We propose an alternating optimization algorithm to the nonconvex Koopman operator learning problem for nonlinear dynamic systems. We show that the proposed algorithm will converge to a critical point with rate $O(1/T)$ and $O(\frac{1}{\log…

Signal Processing · Electrical Eng. & Systems 2020-03-23 Zhiyuan Liu , Guohui Ding , Lijun Chen , Enoch Yeung

Employing the ideas of non-linear preconditioning and testing of the classical proximal point method, we formalise common arguments in convergence rate and convergence proofs of optimisation methods to the verification of a simple…

Optimization and Control · Mathematics 2020-10-06 Tuomo Valkonen

We derive optimal order a posteriori error estimates for fully discrete approximations of linear Schr\"odinger-type equations, in the $L^\infty(L^2)-$norm. For the discretization in time we use the Crank-Nicolson method, while for the space…

Numerical Analysis · Mathematics 2013-04-10 Theodoros Katsaounis , Irene Kyza

Nonconvex and nonsmooth optimization problems are frequently encountered in much of statistics, business, science and engineering, but they are not yet widely recognized as a technology in the sense of scalability. A reason for this…

Optimization and Control · Mathematics 2018-01-19 Bo Jiang , Tianyi Lin , Shiqian Ma , Shuzhong Zhang

This paper proposes an explicit computational method for solving a three-dimensional system of nonlinear elastodynamic sine-Gordon equations subject to appropriate initial and boundary conditions. The time derivative is approximated by…

Numerical Analysis · Mathematics 2025-06-19 Eric Ngondiep

Exponential time differencing methods is a power tool for high-performance numerical simulation of computationally challenging problems in condensed matter physics, fluid dynamics, chemical and biological physics, where mathematical models…

Numerical Analysis · Mathematics 2024-10-15 Evelina V. Permyakova , Denis S. Goldobin

We consider a stochastic control problem for a class of nonlinear kernels. More precisely, our problem of interest consists in the optimisation, over a set of possibly non-dominated probability measures, of solutions of backward stochastic…

Probability · Mathematics 2017-07-28 Dylan Possamaï , Xiaolu Tan , Chao Zhou

We consider a set of interwoven harmonic oscillators where the acceleration of a given oscillator is determined by the position of its nearest neighbor. We show that this problem of N non-local oscillators with periodic boundary conditions…

Numerical Analysis · Mathematics 2013-02-12 Ghazala Akram , Christian Beck

We study an abstract second order inclusion involving two nonlinear single-valued operators and a nonlinear multivalued term. Our goal is to establish the existence of solutions to the problem by applying numerical scheme based on time…

Analysis of PDEs · Mathematics 2019-01-24 Krzysztof Bartosz , Leszek Gasiński , Zhenhai Liu , Paweł Szafraniec

We develop a one step matrix method in order to obtain approximate solutions of first order systems and non-linear ordinary differential equations, reducible to first order systems. We find a sequence of such solutions that converge to the…

Numerical Analysis · Mathematics 2021-07-28 J. J. Alvarez-Sanchez , M. Gadella , L. P. Lara

The challenge of mastering computational tasks of enormous size tends to frequently override questioning the quality of the numerical outcome in terms of accuracy. By this we do not mean the accuracy within the discrete setting, which…

Numerical Analysis · Mathematics 2019-10-17 Markus Bachmayr , Wolfgang Dahmen