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Analysis of Stochastic Petri Nets by the Concept of Near-complete Decomposability.

Giglmayr, J.

In: Statistical Decision Functions, Random Processes, Vol. 1, pages 337-344. Academia, Prague, Czechoslovakia (Availability: Kluwer Academic Publishers Group, Dordrecht, The Netherlands), 1988.

Abstract: The crucial problem when modelling real systems by stochastic Petri nets is the increase of the size of the transition rate matrix representing the stochastic Petri net. A stochastic Petri net is analysed by decomposing the transition rate matrix. In particular, the stationary marking probabilities are determined by solving several smaller matrix equations instead of solving the large equation system.

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