Asymptotic Expansions for Stationary Distributions of Perturbed Semi-Markov Processes

Abstract

New algorithms for computing of asymptotic expansions for stationary distributions of nonlinearly perturbed semi-Markov processes are presented. The algorithms are based on special techniques of sequential phase space reduction, which can be applied to processes with asymptotically coupled and uncoupled finite phase spaces.

83 pages

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Cited by in corpus (5)

• Asymptotic Expansions for Stationary Distributions of Perturbed Semi-Markov Processes
• Reward Algorithms for Semi-Markov Processes
• Asymptotic Expansions for Stationary Distributions of Nonlinearly Perturbed Semi-Markov Processes. II
• Necessary and Sufficient Conditions for Convergence of First-Rare-Event Times for Perturbed Semi-Markov Processes
• Perturbed Markov Chains and Information Networks