منابع مشابه
On Approximating the Stationary Distribution of Time-reversible Markov Chains
Approximating the stationary probability of a state in a Markov chain through Markov chain Monte Carlo techniques is, in general, inefficient. Standard random walk approaches require Õ(τ/π(v)) operations to approximate the probability π(v) of a state v in a chain with mixing time τ , and even the best available techniques still have complexity Õ(τ/π(v)); and since these complexities depend inve...
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Labelled Markov processes are probabilistic versions of labelled transition systems. In general, the state space of a labelled Markov process may be a continuum. In this paper, we study approximation techniques for continuous-state labelled Markov processes. We show that the collection of labelled Markov processes carries a Polish-space structure with a countable basis given by finite-state Mar...
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We study approximate reasoning about continuous-state labeled Markov processes. We show how to approximate a labeled Markov process by a family of finite-state labeled Markov chains. We show that the collection of labeled Markov processes carries a Polish space structure with a countable basis given by finite state Markov chains with rational probabilities. The primary technical tools that we d...
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[Tip: Study the MC, QT, and Little's law lectures together: CTMC (MC lecture), M/M/1 queue (QT lecture), Little's law lecture (when deriving the mean response time from mean number of customers), DTMC (MC lecture), M/M/1 queue derivation using DTMC analysis, derive distribution of response time in M/M/1 queue (QT lecture), relation between Markov property and mem-oryless property (MC lecture), ...
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ژورنال
عنوان ژورنال: Proceedings of the National Academy of Sciences
سال: 1992
ISSN: 0027-8424,1091-6490
DOI: 10.1073/pnas.89.10.4432