By Bruno Sericola
Markov chains are a basic type of stochastic procedures. they're common to resolve difficulties in numerous domain names reminiscent of operational study, computing device technology, verbal exchange networks and production platforms. The good fortune of Markov chains is especially because of their simplicity of use, the massive variety of to be had theoretical effects and the standard of algorithms built for the numerical overview of many metrics of interest.
the writer provides the speculation of either discrete-time and continuous-time homogeneous Markov chains. He conscientiously examines the explosion phenomenon, the Kolmogorov equations, the convergence to equilibrium and the passage time distributions to a country and to a subset of states. those effects are utilized to birth-and-death procedures. He then proposes an in depth learn of the uniformization method by way of Banach algebra. this system is used for the brief research of numerous queuing systems.
1. Discrete-Time Markov Chains
2. Continuous-Time Markov Chains
three. Birth-and-Death Processes
About the Authors
Bruno Sericola is a Senior learn Scientist at Inria Rennes – Bretagne Atlantique in France. His major learn job is in functionality overview of computing device and verbal exchange structures, dependability research of fault-tolerant platforms and stochastic models.
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Extra resources for Markov Chains: Theory and Applications (Iste)
Markov Chains: Theory and Applications (Iste) by Bruno Sericola