Eigenvalue clustering of coefficient matrices in the iterative stride reductions for linear systems

DOI10.1016/j.camwa.2015.11.022zbMath1443.65047OpenAlexW2199416375MaRDI QIDQ2006614

Masatsugu Hada, Munehiro Nagata, Masashi Iwasaki, Yoshimasa Nakamura

Publication date: 11 October 2020

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2015.11.022

zbMATH Keywords

linear systemcoefficient matrixeigenvalue clusteringblock diagonalstride reduction

Mathematics Subject Classification ID

Iterative numerical methods for linear systems (65F10) Direct numerical methods for linear systems and matrix inversion (65F05) Linear equations (linear algebraic aspects) (15A06)

Related Items (2)

A bidiagonalization-based numerical algorithm for computing the inverses of \((p, q)\)-tridiagonal matrices ⋮ Matrix similarity transformations derived from extended q-analogues of the Toda equation and Lotka–Volterra system

Uses Software

• Heat Conduction Toolbox
• Fractional Heat Conduction Toolbox

Cites Work

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• Heat conduction modeling by using fractional-order derivatives
• Inversion of \(k\)-tridiagonal matrices with Toeplitz structure
• Revisiting parallel cyclic reduction and parallel prefix-based algorithms for block tridiagonal systems of equations
• Fast block diagonalization of \(k\)-tridiagonal matrices
• Smoothing by spline functions.
• On condition numbers in the cyclic reduction processes of a tridiagonal matrix
• Cyclic and stride reduction methods for generalised tridiagonal matrices
• On Direct Methods for Solving Poisson’s Equations
• A Generalized Cyclic Reduction Algorithm

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