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This paper proposes a rational filtering domain decomposition technique for the solution of large and sparse symmetric generalized eigenvalue problems. The proposed technique is purely algebraic and decomposes the eigenvalue problem…

Numerical Analysis · Mathematics 2017-11-28 Vassilis Kalantzis , Yuanzhe Xi , Yousef Saad

Many high-dimensional uncertainty quantification problems are solved by polynomial dimensional decomposition (PDD), which represents Fourier-like series expansion in terms of random orthonormal polynomials with increasing dimensions. This…

Numerical Analysis · Mathematics 2018-04-06 Sharif Rahman

A common task when analysing dynamical systems is the determination of normal forms near local bifurcations of equilibria. As most of these normal forms have been classified and analysed, finding which particular class of normal form one…

Dynamical Systems · Mathematics 2017-12-14 Jan Sieber

In this paper, we investigate condition numbers of eigenvalue problems of matrix polynomials with nonsingular leading coefficients, generalizing classical results of matrix perturbation theory. We provide a relation between the condition…

Spectral Theory · Mathematics 2009-07-23 Nikolaos Papathanasiou , Panayiotis Psarrakos

In the present note we consider a type of matrices stemming in the context of the numerical approximation of distributed order fractional differential equations (FDEs): from one side they could look standard, since they are, real, symmetric…

Numerical Analysis · Mathematics 2021-12-08 M. Bogoya , S. M. Grudsky , S. Serra-Capizzano , C. Tablino-Possio

Inverse problem or parameter estimation of ordinary differential equations (ODEs), the iterative process of minimizing the mismatch between model-predicted and experimental states by tuning the parameter values within an optimization…

Systems and Control · Electrical Eng. & Systems 2026-04-21 Siddharth Prabhu , Srinivas Rangarajan , Mayuresh Kothare

Hybrid numerical-experimental testing is a standard approach for complex dynamical structures that are, on the one hand, not easy to model due to complexity and parameter uncertainty and, on the other hand, too expensive for full-scale…

Dynamical Systems · Mathematics 2020-03-24 Benjamin Unger

This paper presents a novel and direct approach to price boundary and final-value problems, corresponding to barrier options, using forward deep learning to solve forward-backward stochastic differential equations (FBSDEs). Barrier…

Computational Finance · Quantitative Finance 2024-09-13 Narayan Ganesan , Yajie Yu , Bernhard Hientzsch

The delay Lyapunov equation is an important matrix boundary-value problem which arises as an analogue of the Lyapunov equation in the study of time-delay systems $\dot{x}(t) = A_0x(t)+A_1x(t-\tau)+B_0u(t)$. We propose a new algorithm for…

Numerical Analysis · Mathematics 2018-10-16 Elias Jarlebring , Federico Poloni

We consider the problem of estimating parameters of stochastic differential equations (SDEs) with discrete-time observations that are either completely or partially observed. The transition density between two observations is generally…

Methodology · Statistics 2015-09-09 Libo Sun , Chihoon Lee , Jennifer A. Hoeting

This work develops a class of probabilistic algorithms for the numerical solution of nonlinear, time-dependent partial differential equations (PDEs). Current state-of-the-art PDE solvers treat the space- and time-dimensions separately,…

Numerical Analysis · Mathematics 2022-03-10 Nicholas Krämer , Jonathan Schmidt , Philipp Hennig

We present a Chebyshev collocation method for linear ODE and DDE problems. We first give a posteriori estimates for the accuracy of the approximate solution of a scalar ODE initial value problem. Examples of the success of the estimate are…

Numerical Analysis · Mathematics 2024-08-15 Ed Bueler

We propose a simple domain decomposition method for $d$-dimensional elliptic PDEs which involves an overlapping decomposition into local subdomain problems and a global coarse problem. It relies on a space-filling curve to create equally…

Numerical Analysis · Mathematics 2021-03-08 Michael Griebel , Marc-Alexander Schweitzer , Lukas Troska

The aim of this paper is to develop an algebraic multigrid method to solve eigenvalue problems based on the combination of the multilevel correction scheme and the algebraic multigrid method for linear equations. Our approach uses the…

Numerical Analysis · Mathematics 2020-03-02 Ning Zhang , Xiaole Han , Yunhui He , Hehu Xie , Chun'guang You

We describe a method to model nonlinear dynamical systems using periodic solutions of delay-differential equations. We show that any finite-time trajectory of a nonlinear dynamical system can be loaded approximately into the initial…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Alexander N. Jourjine

In this paper, we deal with a new type of differential equations called anticipated backward doubly stochastic differential equations (anticipated BDSDEs). The coefficients of these BDSDEs depend on the future value of the solution $(Y,…

Probability · Mathematics 2013-07-10 Xiaoming Xu

Developing algorithms for solving high-dimensional partial differential equations (PDEs) has been an exceedingly difficult task for a long time, due to the notoriously difficult problem known as the "curse of dimensionality". This paper…

Numerical Analysis · Mathematics 2020-07-17 Jiequn Han , Arnulf Jentzen , Weinan E

This paper treats comprehensively the construction of problems from nonlinear dynamics and constrained optimization amenable to parameter continuation techniques and with particular emphasis on multi-segment boundary-value problems with…

Dynamical Systems · Mathematics 2022-09-27 Zaid Ahsan , Harry Dankowicz , Mingwu Li , Jan Sieber

This paper discusses a multi-term time-fractional delay differential equation in a real Hilbert space. An iterative scheme for a multi-term time-fractional differential equation is established using Rothe's method. The method of…

Numerical Analysis · Mathematics 2024-03-13 Areefa Khatoon , Abdur Raheem , Asma Afreen

Parametrized families of PDEs arise in various contexts such as inverse problems, control and optimization, risk assessment, and uncertainty quantification. In most of these applications, the number of parameters is large or perhaps even…

Analysis of PDEs · Mathematics 2015-03-04 Albert Cohen , Ronald Devore
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