Multipreconditioned GMRES for simulating stochastic automata networks
| Autor: | Chun Wen, Zhao-Li Shen, Hong-Fan Zhang, Chen Liu, Xian-Ming Gu, Ting-Zhu Huang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
preconditioner
General Mathematics MathematicsofComputing_NUMERICALANALYSIS 010103 numerical & computational mathematics 01 natural sciences Generalized minimal residual method 90b15 010101 applied mathematics stochastic automata network QA1-939 Applied mathematics 0101 mathematics Stochastic automata gmres 65f10 Mathematics arnoldi process |
| Zdroj: | Open Mathematics, Vol 16, Iss 1, Pp 986-998 (2018) |
| ISSN: | 2391-5455 |
| Popis: | Stochastic Automata Networks (SANs) have a large amount of applications in modelling queueing systems and communication systems. To find the steady state probability distribution of the SANs, it often needs to solve linear systems which involve their generator matrices. However, some classical iterative methods such as the Jacobi and the Gauss-Seidel are inefficient due to the huge size of the generator matrices. In this paper, the multipreconditioned GMRES (MPGMRES) is considered by using two or more preconditioners simultaneously. Meanwhile, a selective version of the MPGMRES is presented to overcome the rapid increase of the storage requirements and make it practical. Numerical results on two models of SANs are reported to illustrate the effectiveness of these proposed methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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