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Books > Computing & IT > Applications of computing > Artificial intelligence
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Semi-Markov Processes and Reliability (Paperback, Softcover reprint of the original 1st ed. 2001)
Loot Price: R2,790
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Semi-Markov Processes and Reliability (Paperback, Softcover reprint of the original 1st ed. 2001)
Series: Statistics for Industry and Technology
Expected to ship within 10 - 15 working days
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The theory of stochastic processes, for science and engineering,
can be considered as an extension of probability theory allowing
modeling of the evolution of systems over time. The modern theory
of Markov processes has its origins in the studies of A.A. Markov
(1856-1922) on sequences of experiments connected in a chain and in
the attempts to describe mathematically the physical phenomenon
Brownian motion. The theory of stochastic processes entered in a
period of intensive development when the idea of Markov property
was brought in. This book is a modern overall view of semi-Markov
processes and its applications in reliability. It is accessible to
readers with a first course in Probability theory (including the
basic notions of Markov chain). The text contains many examples
which aid in the understanding of the theoretical notions and shows
how to apply them to concrete physical situations including
algorithmic simulations. Many examples of the concrete applications
in reliability are given.Features: * Processes associated to
semi-Markov kernel for general and discrete state spaces *
Asymptotic theory of processes and of additive functionals *
Statistical estimation of semi-Markov kernel and of reliability
function * Monte Carlo simulation * Applications in reliability and
maintenance The book is a valuable resource for understanding the
latest developments in Semi-Markov Processes and reliability.
Practitioners, researchers and professionals in applied
mathematics, control and engineering who work in areas of
reliability, lifetime data analysis, statistics, probability, and
engineering will find this book an up-to-date overview of the
field.
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