On HSS-Based Iteration Methods for Two Classes of Tensor Equations

On HSS-Based Iteration Methods for Two Classes of Tensor Equations

Year:    2020

Author:    Ming-Yu Deng, Xue-Ping Guo

East Asian Journal on Applied Mathematics, Vol. 10 (2020), Iss. 2 : pp. 381–398

Abstract

HSS-based iteration methods for large systems of tensor equations $\mathcal{T}$($x$) = $b$ and $Ax$ = $\mathcal{T}$($x$) + $b$ are considered and conditions of their local convergence are presented. Numerical experiments show that for the equations $\mathcal{T}$($x$) = $b$, the Newton-HSS method outperforms the Newton-GMRES method. For nonlinear convection-diffusion equations the methods based on HSS iterations are generally more efficient and robust than the Newton-GMRES method.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/eajam.140819.071019

East Asian Journal on Applied Mathematics, Vol. 10 (2020), Iss. 2 : pp. 381–398

Published online:    2020-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    18

Keywords:    Tensor equation HSS iteration k-mode product convergence large sparse system.

Author Details

Ming-Yu Deng

Xue-Ping Guo