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In this article we investigate model order reduction of large-scale systems using time-limited balanced truncation, which restricts the well known balanced truncation framework to prescribed finite time intervals. The main emphasis is on…

Numerical Analysis · Mathematics 2018-01-08 Patrick Kürschner

This paper is concerned with a novel regularisation technique for solving linear ill-posed operator equations in Hilbert spaces from data that is corrupted by white noise. We combine convex penalty functionals with extreme-value statistics…

Statistics Theory · Mathematics 2012-04-03 Klaus Frick , Philipp Marnitz , Axel Munk

This paper provides a new regularization method which is particularly suitable for linear exponentially ill-posed problems. Under logarithmic source conditions (which have a natural interpretation in terms of Sobolev spaces in the…

Numerical Analysis · Mathematics 2020-07-08 Walter Cedric Simo Tao Lee

We propose a class of weighted compact central (WCC) schemes for solving hyperbolic conservation laws. The linear version can be considered as a high-order extension of the central Lax-Friedrichs (LxF) scheme and the central conservation…

Numerical Analysis · Mathematics 2022-07-20 Hua Shen , Matteo Parsani

This paper investigates model-order reduction methods for geometrically nonlinear structures. The parametrisation method of invariant manifolds is used and adapted to the case of mechanical systems expressed in the physical basis, so that…

Numerical Analysis · Mathematics 2021-09-22 Alessandra Vizzaccaro , Andrea Opreni , Loïc Salles , Attilio Frangi , Cyril Touzé

The primary focus of this paper is on designing an inexact first-order algorithm for solving constrained nonlinear optimization problems. By controlling the inexactness of the subproblem solution, we can significantly reduce the…

Optimization and Control · Mathematics 2019-11-19 Hao Wang , Fan Zhang , Jiashan Wang , Yuyang Rong

Several convergence results in Hilbert scales under different source conditions are proved and orders of convergence and optimal orders of convergence are derived. Also, relations between those source conditions are proved. The concept of a…

Functional Analysis · Mathematics 2015-06-03 Gisela L. Mazzieri , Ruben D. Spies

We devise and analyze two hybrid high-order (HHO) methods for the numerical approximation of the biharmonic problem. The methods support polyhedral meshes, rely on the primal formulation of the problem, and deliver $O(h^{k+1})$ $H^2$-error…

Numerical Analysis · Mathematics 2022-04-11 Zhaonan Dong , Alexandre Ern

We present an arbitrary-order spectral element method for general-purpose simulation of non-overturning water waves, described by fully nonlinear potential theory. The method can be viewed as a high-order extension of the classical finite…

Computational Physics · Physics 2016-06-22 Allan Peter Engsig-Karup , Claes Eskilsson , Daniele Bigoni

Coordinate descent methods have considerable impact in global optimization because global (or, at least, almost global) minimization is affordable for low-dimensional problems. Coordinate descent methods with high-order regularized models…

Optimization and Control · Mathematics 2023-04-28 V. S. Amaral , R. Andreani , E. G. Birgin , D. S. Marcondes , J. M. Martínez

In this paper, we propose a new MUSCL scheme by combining the ideas of the Kurganov and Tadmor scheme and the so-called Deviation method which results in a well-balanced finite volume method for the hyperbolic balance laws, by evolving the…

Numerical Analysis · Mathematics 2024-05-15 Yu-Chen Cheng , Christian Klingenberg , Rony Touma

The scaling of the exact solution of a hyperbolic balance law generates a family of scaled problems in which the source term does not depend on the current solution. These problems are used to construct a sequence of solutions whose…

Numerical Analysis · Mathematics 2020-07-21 Gino I. Montecinos

This paper considers the approximation of partial differential equations with a point collocation framework based on high-order local maximum-entropy schemes (HOLMES). In this approach, smooth basis functions are computed through an…

Computational Engineering, Finance, and Science · Computer Science 2020-11-02 F. Greco , M. Arroyo

This work addresses the Assembly Line Rebalancing Problem in manual assembly systems where multiple workers operate in parallel within the same station - an industrially relevant scenario that remains insufficiently explored in the…

Systems and Control · Electrical Eng. & Systems 2025-12-16 Martina Vinetti , Sabino Francesco Roselli , Martin Fabian

The object of the present paper is to extend the third-order iterative method for solving nonlinear equations into systems of nonlinear equations. Since our motive is to develop the method which improve the order of convergence of Newton's…

Numerical Analysis · Mathematics 2013-09-24 Anuradha Singh , J. P. Jaiswa

This note aims at demonstrating the advantage of moving-water well-balanced schemes over still-water well-balanced schemes for the shallow water equations. We concentrate on numerical examples with solutions near a moving-water equilibrium.…

Numerical Analysis · Mathematics 2015-02-04 Yulong Xing , Chi-Wang Shu , Sebastian Noelle

This paper introduces new solvers for the computation of low-rank approximate solutions to large-scale linear problems, with a particular focus on the regularization of linear inverse problems. Although Krylov methods incorporating explicit…

Numerical Analysis · Mathematics 2019-11-05 Silvia Gazzola , Chang Meng , James Nagy

The discontinuous Galerkin finite element method (DGFEM) developed by Rhebergen et al. (2008) offers a robust method for solving systems of nonconservative hyperbolic partial differential equations but, as we show here, does not…

Computational Physics · Physics 2020-06-08 Thomas Kent , Onno Bokhove

Measuring how quickly iterative methods converge is essential in computational mathematics, but current approaches have significant limitations. Q-order analysis requires strict smoothness conditions, while R-order analysis lacks precision…

Numerical Analysis · Mathematics 2025-04-09 Xiangmin Jiao , Hongji Gao

Regularization methods are a key tool in the solution of inverse problems. They are used to introduce prior knowledge and make the approximation of ill-posed (pseudo-)inverses feasible. In the last two decades interest has shifted from…

Numerical Analysis · Mathematics 2018-01-31 Martin Benning , Martin Burger