Markov Chains. Theory And Applications

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Markov chains are a fundamental class of stochastic processes


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Birth-and-Death Processes 4

Contents 1

Continuous-Time Markov Chains 3

Discrete-Time Markov Chains 2

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

He then proposes a detailed study of the uniformization technique by means of Banach algebra

His main research activity is in performance evaluation of computer and communication systems, dependability analysis of fault-tolerant systems and stochastic models.

Queues About the Authors Bruno Sericola is a Senior Research Scientist at Inria Rennes Bretagne Atlantique in France

The author presents the theory of both discrete-time and continuous-time homogeneous Markov chains

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

These results are applied to birth-and-death 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

This technique is used for the transient analysis of several queuing systems

Uniformization 5

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