September 2014
Intermediate to advanced
270 pages
8h 1m
English
Content preview from Semi-Markov Processes
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Summary
We can observe the phenomena and systems that change randomly during the time in various practical situations. The theory of stochastic (random) processes allows the modeling of random evolution of systems through the time.
The main stochastic processes considered in this book are the continuous time semi-Markov processes (SMP) with a discrete set of states. SMP is characterized in that, a future states of the process and their sojourn times do not depend on the past states and their sojourn times if a present state is known. A holding time in a state i before passing to a state j and a waiting time in state i of SMP are nonnegative random variables with arbitrary cumulative distribution function, while for a Markov process these random ...
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