Iterative algorithm for minimal norm least squares solution to general linear matrix equations

DOI10.1080/00207160802684459zbMath1203.65080OpenAlexW2068134326MaRDI QIDQ3056390

Zhao-Yan Li, Yong Wang

Publication date: 12 November 2010

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207160802684459

zbMATH Keywords

convergencenumerical examplesiterative algorithmsmatrix equations and identitiesLyapunov matrix equationslinear matrix equationsSylvester matrix equationsmatrix algorithmsconditioning of matricesmatrix inversion, generalized inversesminimal norm least squares solutions

Mathematics Subject Classification ID

Related Items (6)

Least squares solution with the minimum-norm to general matrix equations via iteration ⋮ Reduced-order modeling methods via bivariate discrete orthogonal polynomials for two-dimensional discrete state-delayed systems ⋮ On the global Krylov subspace methods for solving general coupled matrix equations ⋮ A cyclic iterative approach and its modified version to solve coupled Sylvester-transpose matrix equations ⋮ Positive definite solutions of the nonlinear matrix equation \(X + A^H\bar{X}^{-1}A = I\) ⋮ Weighted steepest descent method for solving matrix equations

Uses Software

• KELLEY

Cites Work

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