In: Proc. 4th Int. Workshop on Petri Nets and Performance Models (PNPM'91), Melbourne, Australia, pages 54-63. IEEE Comp. Soc. Press, December 1991.
Abstract: Plateau has introduced an efficient way for solving stochastic processes that are derived from the composition of stochastic automata by making extensive use of the Kronecker (tensor) algebra for matrices. In this paper we apply that efficient solution to a class of Stochastic Petri nets (SPN) that has been called Superposed Stochastic Automata (SSA). The solution has been implemented both with sequential and parallel programs. SSA are a rather restricted subclass of SPN, but the extension to the general case doesn't appear to pose any theoretical problem.
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