Perturbation analysis of singular linear systems with index one∗

DOI10.1080/00207160008804956zbMath0958.65043OpenAlexW2010435296MaRDI QIDQ4489984

Yi-Min Wei

Publication date: 28 March 2001

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

Full work available at URL: https://doi.org/10.1080/00207160008804956

zbMATH Keywords

group inversesingular linear systemgeneralized linear least squares problemmatrix of index one

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20)

Related Items (15)

On GMRES for Singular EP and GP Systems ⋮ Acute perturbation of the group inverse ⋮ FOM accelerated by an extrapolation method for solving PageRank problems ⋮ On computation of the steady-state probability distribution of probabilistic Boolean networks with gene perturbation ⋮ Perturbation analysis of singular linear systems with arbitrary index. ⋮ Perturbation bounds for the group inverse and its oblique projection ⋮ Comment on ``condition number of Drazin inverse and their condition numbers of singular linear systems ⋮ On Perturbation Bounds for the Joint Stationary Distribution of Multivariate Markov Chain Models ⋮ The representation and approximation for Drazin inverse ⋮ Bounds on condition number of a singular matrix and its applications ⋮ Structured perturbations of group inverse and singular linear system with index one ⋮ Condition number for the Drazin inverse and the Drazin-inverse solution of singular linear system with their condition numbers ⋮ On group inverse of singular Toeplitz matrices ⋮ Quotient convergence and multi-splitting methods for solving singular linear equations ⋮ Convergence and quotient convergence of iterative methods for solving singular linear equations with index one

Cites Work

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• Iterative Consistency: A Concept for the Solution of Singular Systems of Linear Equations
• A Characterization and Representation of the Drazin Inverse
• On the use of two QMR algorithms for solving singular systems and applications in Markov chain modeling

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