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Over the past decade, various matrix completion algorithms have been developed. Thresholded singular value decomposition (SVD) is a popular technique in implementing many of them. A sizable number of studies have shown its theoretical and…

Methodology · Statistics 2016-05-10 Juhee Cho , Donggyu Kim , Karl Rohe

A new Jacobian approximation is developed for use in quasi-Newton methods for solving systems of nonlinear equations. The new hypersecant Jacobian approximation is intended for the special case where the evaluation of the functions whose…

Numerical Analysis · Mathematics 2009-05-08 Johan Carlsson , John R. Cary

We consider the inverse dynamic problem for a dynamical system with discrete time associated with a semi-infinite complex Jacobi matrix. We propose two approaches of recovering coefficients from dynamic response operator and answer a…

Analysis of PDEs · Mathematics 2025-05-28 A. S. Mikhaylov , V. S. Mikhaylov

In this work, we present a new scalable incomplete LU factorization framework called Javelin to be used as a preconditioner for solving sparse linear systems with iterative methods. Javelin allows for improved parallel factorization on…

Mathematical Software · Computer Science 2019-05-06 Joshua Dennis Booth , Gregory Bolet

This work develops user-friendly a posteriori error estimates of finite element methods, based on smoothers of linear iterative solvers. The proposed method employs simple smoothers, such as Jacobi or Gauss-Seidel iteration, on an auxiliary…

Numerical Analysis · Mathematics 2026-02-24 Yuwen Li , Han Shui

Differential-algebraic equations (DAEs) have been used in modeling various dynamical systems in science and engineering. Several preprocessing methods for DAEs, such as consistent initialization and index reduction, use structural…

Symbolic Computation · Computer Science 2024-03-18 Taihei Oki , Yujin Song

This research investigates using a mixed-precision iterative refinement method using posit numbers instead of the standard IEEE floating-point format. The method is applied to solve a general linear system represented by the equation $Ax =…

Numerical Analysis · Mathematics 2024-08-28 James Quinlan , E. Theodore L. Omtzigt

We propose a novel iterative numerical method to solve the three-dimensional inverse obstacle scattering problem of recovering the shape of the obstacle from far-field measurements. To address the inherent ill-posed nature of the inverse…

Numerical Analysis · Mathematics 2024-04-18 Junqing Chen , Bangti Jin , Haibo Liu

In this paper, we introduce and study a new extragradient iterative process for finding a common element of the set of fixed points of an infinite family of nonexpansive mappings and the set of solutions of a variational inequality for an…

Functional Analysis · Mathematics 2014-05-22 Ibrahim Karahan , Murat Ozdemir

A surface integral equation (SIE) formulation under the magneto-quasi-static assumption is proposed to efficiently and accurately model arbitrarily shaped interconnects in packages. Through decently transferring all electromagnetic…

Computational Engineering, Finance, and Science · Computer Science 2022-10-12 Zekun Zhu , Zhizhang Chen , Shunchuan Yang

We consider the low-rank alternating directions implicit (ADI) iteration for approximately solving large-scale algebraic Sylvester equations. Inside every iteration step of this iterative process a pair of linear systems of equations has to…

Numerical Analysis · Mathematics 2023-12-06 Patrick Kürschner

Deterministic recursive algorithms for the computation of matrix triangular decompositions with permutations like LU and Bruhat decomposition are presented for the case of commutative domains. This decomposition can be considered as a…

Symbolic Computation · Computer Science 2017-02-24 Gennadi Malaschonok , Anton Scherbinin

Considered herein is a modified Newton method for the numerical solution of nonlinear equations where the Jacobian is approximated using a complex-step derivative approximation. We show that this method converges for sufficiently small…

Numerical Analysis · Mathematics 2024-10-03 Dimitrios Mitsotakis

Sylvester matrix equations are ubiquitous in scientific computing. However, few solution techniques exist for their generalized multiterm version, as they now arise in an increasingly large number of applications. In this work, we consider…

Numerical Analysis · Mathematics 2024-03-04 Yannis Voet

A linear inverse problem is proposed that requires the determination of multiple unknown signal vectors. Each unknown vector passes through a different system matrix and the results are added to yield a single observation vector. Given the…

Numerical Analysis · Computer Science 2010-09-03 Adam C. Zelinski , Vivek K Goyal , Elfar Adalsteinsson

In this paper, we assess the performance of adaptive and nested factorized sparse approximate inverses as smoothers in multilevel V-cycles, when smoothing is performed following the Chebyshev iteration of the fourth kind. For our test…

Numerical Analysis · Mathematics 2025-09-25 Pablo Jiménez Recio , Marc Alexander Schweitzer

We over-approximate reachability sets in string rewriting by languages defined by admissible factors, called tiles. A sparse set of tiles contains only those that are reachable in derivations, and is constructed by completing an automaton.…

Logic in Computer Science · Computer Science 2020-03-04 Alfons Geser , Dieter Hofbauer , Johannes Waldmann

In this paper, we first establish the convergence criteria of the residual iteration method for solving quadratic eigenvalue problem- s. We analyze the impact of shift point and the subspace expansion on the convergence of this method. In…

Numerical Analysis · Mathematics 2017-01-12 Liu Yang , Yuquan Sun , Fanghui Gong

The computation of matrix functions is a well-studied problem. Of special importance are the exponential and the logarithm of a matrix, where the latter also raises existence and uniqueness questions. This is particularly relevant in the…

Rings and Algebras · Mathematics 2024-06-17 Ellen Baake , Michael Baake

In this paper we propose an approach to approximate a truncated singular value decomposition of a large structured matrix. By first decomposing the matrix into a sum of Kronecker products, our approach can be used to approximate a large…

Numerical Analysis · Mathematics 2018-04-03 Clarissa Garvey , Chang Meng , James G. Nagy
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