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In this paper, we analyze the spectra of the preconditioned matrices arising from discretized multi-dimensional Riesz spatial fractional diffusion equations. The finite difference method is employed to approximate the multi-dimensional…

Numerical Analysis · Mathematics 2022-06-07 Xin Huang , Xue-Lei Lin , Michael K. Ng , Hai-Wei Sun

In this dissertation, it is first shown that, when the radial basis function is a $p$-norm and $1 < p < 2$, interpolation is always possible when the points are all different and there are at least two of them. We then show that…

Numerical Analysis · Mathematics 2010-06-15 Brad Baxter

When solving linear systems with nonsymmetric Toeplitz or multilevel Toeplitz matrices using Krylov subspace methods, the coefficient matrix may be symmetrized. The preconditioned MINRES method can then be applied to this symmetrized…

Numerical Analysis · Mathematics 2019-04-15 Jennifer Pestana

This paper investigates using the conjugate gradient iterative solver for ill-posed problems. We show that preconditioner and Tikhonov-regularization work in conjunction. In particular when they employ the same symmetric positive…

Numerical Analysis · Mathematics 2025-12-12 Ahmed Chabib , Jean-Francois Witz , Vincent Magnier , Pierre Gosselet

In recent years, there has been a renewed interest in preconditioning for multilevel Toeplitz systems, a research field that has been extensively explored over the past several decades. This work introduces novel preconditioning strategies…

Numerical Analysis · Mathematics 2024-10-01 Sean Y. Hon , Congcong Li , Rosita L. Sormani , Rolf Krause , Stefano Serra-Capizzano

Radial basis functions are typically used when discretization sche-mes require inhomogeneous node distributions. While spawning from a desire to interpolate functions on a random set of nodes, they have found successful applications in…

Numerical Analysis · Mathematics 2022-10-20 P. -A. Gourdain , M. B. Adams , M. Evans , H. R. Hasson , J. R. Young , I. West-Abdallah

Efficient numerical solvers for partial differential equations empower science and engineering. One of the commonly employed numerical solvers is the preconditioned conjugate gradient (PCG) algorithm which can solve large systems to a given…

Numerical Analysis · Mathematics 2023-09-07 Yichen Li , Peter Yichen Chen , Tao Du , Wojciech Matusik

Using a deterministic framework allows us to estimate a function with the purpose of interpolating data in spatial statistics. Radial basis functions are commonly used for scattered data interpolation in a d-dimensional space, however,…

Computation · Statistics 2024-04-03 Joaquin Cavieres , Michael Karkulik

This note proposes an efficient preconditioner for solving linear and semi-linear parabolic equations. With the Crank-Nicholson time stepping method, the algebraic system of equations at each time step is solved with the conjugate gradient…

Numerical Analysis · Mathematics 2021-05-11 Jordi Feliu-Fabà , Lexing Ying

This work aims to accelerate the convergence of proximal gradient methods used to solve regularized linear inverse problems. This is achieved by designing a polynomial-based preconditioner that targets the eigenvalue spectrum of the normal…

In this thesis we study the preconditioning of square, non-symmetric and real Toeplitz systems. We prove theoretical results, which constitute sufficient conditions for the efficiency of the proposed preconditioners and the fast convergence…

Numerical Analysis · Mathematics 2023-03-07 Grigorios Tachyridis

Circulant preconditioners are commonly used to accelerate the rate of convergence of iterative methods when solving linear systems of equations with a Toeplitz matrix. Block extensions that can be applied when the system has a block…

Numerical Analysis · Mathematics 2016-09-06 L. Dykes , S. Noschese , L. Reichel

In this work, we develop a novel multilevel Tau matrix-based preconditioned method for a class of non-symmetric multilevel Toeplitz systems. This method not only accounts for but also improves upon an ideal preconditioner pioneered by [J.…

Numerical Analysis · Mathematics 2024-09-05 Congcong Li , Sean Hon

We show that the mass matrix derived from finite elements can be effectively used as a preconditioner for iteratively solving the linear system arising from finite-difference discretization of the Poisson equation, using the conjugate…

Numerical Analysis · Mathematics 2021-11-08 Chen Greif , Yunhui He

We propose several circulant preconditioners for systems defined by some functions $g$ of Toeplitz matrices $A_n$. In this paper we are interested in solving $g(A_n)\mathbf{x}=\mathbf{b}$ by the preconditioned conjugate method or the…

Numerical Analysis · Mathematics 2018-07-31 Sean Hon

Preconditioning for multilevel Toeplitz systems has long been a focal point of research in numerical linear algebra. In this work, we develop a novel preconditioning method for a class of nonsymmetric multilevel Toeplitz systems, which…

Numerical Analysis · Mathematics 2024-09-25 Yuan-Yuan Huang , Sean Y. Hon , Lot-Kei Chou , Siu-Long Lei

The conjugate gradient method is a widely used algorithm for the numerical solution of a system of linear equations. It is particularly attractive because it allows one to take advantage of sparse matrices and produces (in case of infinite…

Numerical Analysis · Mathematics 2017-11-27 Sergey Voronin , Christophe Zaroli , Naresh P. Cuntoor

A block lower triangular Toeplitz system arising from time-space fractional diffusion equation is discussed. For efficient solutions of such the linear system, the preconditioned biconjugate gradient stabilized method and flexible general…

Numerical Analysis · Mathematics 2019-05-28 Yong-Liang Zhao , Pei-Yong Zhu , Xian-Ming Gu , Xi-Le Zhao , Jianxiong Cao

In this paper we want to propose practical numerical methods to solve a class of initial-boundary problem of space-time fractional advection-diffusion equations. To start with, an implicit method based on two-sided Gr\"unwald formulae is…

Numerical Analysis · Mathematics 2016-06-22 Zhi Zhao , Xiao-Qing Jin , Matthew M. Lin

The hierarchical interpolative factorization for elliptic partial differential equations is a fast algorithm for approximate sparse matrix inversion in linear or quasilinear time. Its accuracy can degrade, however, when applied to strongly…

Numerical Analysis · Mathematics 2019-04-09 Jordi Feliu-Fabà , Kenneth L. Ho , Lexing Ying
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