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Markov Chains Theory and Applications
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Description

Markov chains are a fundamental class of stochastic processes. They are widely used to solve problems in a large number of domains such as operational research, computer science, communication networks and manufacturing systems. The success of Markov chains is mainly due to their simplicity of use, the large number of available theoretical results and the quality of algorithms developed for the numerical evaluation of many metrics of interest. The author presents the theory of both discrete–time and continuous–time homogeneous Markov chains. He carefully examines the explosion phenomenon, the Kolmogorov equations, the convergence to equilibrium and the passage time distributions to a state and to a subset of states. These results are applied to birth–and–death processes. He then proposes a detailed study of the uniformization technique by means of Banach algebra. This technique is used for the transient analysis of several queuing systems.

More Details About Markov Chains Theory and Applications
General Information
Author(s)Bruno Sericola
PublisherWiley
ISBN9781848214934
Pages416
BindingHardcover
LanguageEnglish
Publish YearJanuary 2013
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