Markov chains
نویسنده
چکیده
[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), M/M/m queue (QT lecture).] Markov process [1, pg. 337] is a stochastic process whose dynamic behavior is such that probability distribution for its future development depends only on its present state and not how the process arrived in that state. If state space is discrete, then it is a Markov chain, i.e., the random variables or are discrete.
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