Regenerative randomization: theory and application examples
Randomization is a popular method for the transient solution of continuous-time Markov models. Its primary advantages over other methods (i.e., ODE solvers) are robustness and ease of implementation. It is however well-known that the performance of the method deteriorates with the
| Authors: | , |
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| Format: | article |
| Publication Date: | 1995 |
| Country: | España |
| Institution: | Universitat Politècnica de Catalunya (UPC) |
| Repository: | UPCommons. Portal del coneixement obert de la UPC |
| Language: | English |
| OAI Identifier: | oai:upcommons.upc.edu:2117/23553 |
| Online Access: | https://hdl.handle.net/2117/23553 |
| Access Level: | Open access |
| Keyword: | Markov processes Fault-tolerant computing Markov, Processos de Tolerància als errors (Informàtica) Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica Àrees temàtiques de la UPC::Matemàtiques i estadística::Probabilitat |
| Summary: | Randomization is a popular method for the transient solution of continuous-time Markov models. Its primary advantages over other methods (i.e., ODE solvers) are robustness and ease of implementation. It is however well-known that the performance of the method deteriorates with the |
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