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Semi-Markov Process
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High Quality Content by WIKIPEDIA articles! A semi-Markov process is a process that changes states according to a discrete time Markov Chain but stays at each state for a random amount of time with distribution Hn. A Continuous Time Markov Chain is a special case of a semi-Markov process in which the transition times are exponentially distributed with rate . A Markov process, named after the Russian mathematician Andrey Markov, is a mathematical model for the random evolution of a memoryless system, that is, one for which the likelihood of a given future state, at any given moment, depends only on its present state, and not on any past states. In a common description, a stochastic process with the Markov property, or memorylessness, is one for which conditional on the present state of the system, its future and past are independent.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09786130333669
- Editor Lambert M. Surhone, Miriam T. Timpledon, Susan F. Marseken
- Sprache Englisch
- Größe H220mm x B150mm x T4mm
- Jahr 2010
- EAN 9786130333669
- Format Fachbuch
- ISBN 978-613-0-33366-9
- Titel Semi-Markov Process
- Untertitel Continuous-time Markov Process, Markov Process, Markov Chain, Stochastic Process, Examples of Markov Chains, Markov Decision Process
- Gewicht 124g
- Herausgeber Betascript Publishers
- Anzahl Seiten 72
- Genre Mathematik
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