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Numerical iterative methods for Markovian dependability and performability models: new results and a comparison

Author
Suñe, V.; Domingo, J.; Carrasco, J.
Type of activity
Journal article
Journal
Performance evaluation
Date of publication
2000-02
Volume
39
Number
1-4
First page
99
Last page
125
Repository
http://hdl.handle.net/2117/21068 Open in new window
Abstract
In this paper we deal with iterative numerical methods to solve linear systems arising in continuous-time Markov chain (CTMC) models. We develop an algorithm to dynamically tune the relaxation parameter of the successive over-relaxation method. We give a sufficient condition for the Gauss-Seidel method to converge when computing the steady-state probability vector of a finite irreducible CTMC, an a suffient condition for the Generalized Minimal Residual projection method not to converge to the t...
Citation
Suñe, V.; Domingo, J.; Carrasco, J. Numerical iterative methods for Markovian dependability and performability models: new results and a comparison. "Performance evaluation", Febrer 2000, vol. 39, núm. 1-4, p. 99-125.
Group of research
QINE - Low Power Design, Test, Verification and Security ICs

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