Stochastic Processes
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Stochastic Processes

with Applications to Reliability Theory
 eBook
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9780857292742
Veröffentl:
2011
Einband:
eBook
Seiten:
254
Autor:
Toshio Nakagawa
Serie:
Springer Series in Reliability Engineering
eBook Typ:
PDF
eBook Format:
Reflowable eBook
Kopierschutz:
Digital Watermark [Social-DRM]
Sprache:
Englisch
Beschreibung:

Stochastic Processes covers useful reliability studies and applications, while providing an overview of stochastic processes. Examples from reliability models illustrate how to apply stochastic processes.

Reliability theory is of fundamental importance for engineers and managers involved in the manufacture of high-quality products and the design of reliable systems. In order to make sense of the theory, however, and to apply it to real systems, an understanding of the basic stochastic processes is indispensable.

As well as providing readers with useful reliability studies and applications, Stochastic Processes also gives a basic treatment of such stochastic processes as:

  • the Poisson process,
  • the renewal process,
  • the Markov chain,
  • the Markov process, and
  • the Markov renewal process.

Many examples are cited from reliability models to show the reader how to apply stochastic processes. Furthermore, Stochastic Processes gives a simple introduction to other stochastic processes such as the cumulative process, the Wiener process, the Brownian motion and reliability applications.

Stochastic Processes is suitable for use as a reliability textbook by advanced undergraduate and graduate students. It is also of interest to researchers, engineers and managers who study or practise reliability and maintenance. 

1. Introduction.- 2. Poisson Processes.- 3. Renewal Processes.- 4. Markov Chains.- 5. Semi-Markov and Markov Renewal Processes.- 6. Cumulative Processes.- 7. Brownian Motion and Lévy Processes.- 8. Redundant Systems.

Reliability theory is of fundamental importance for engineers and managers involved in the manufacture of high-quality products and the design of reliable systems. In order to make sense of the theory, however, and to apply it to real systems, an understanding of the basic stochastic processes is indispensable.

As well as providing readers with useful reliability studies and applications, Stochastic Processes also gives a basic treatment of such stochastic processes as:

  • the Poisson process,
  • the renewal process,
  • the Markov chain,
  • the Markov process, and
  • the Markov renewal process.

Many examples are cited from reliability models to show the reader how to apply stochastic processes. Furthermore, Stochastic Processes gives a simple introduction to other stochastic processes such as the cumulative process, the Wiener process, the Brownian motion and reliability applications.

Stochastic Processes is suitable for use as a reliability textbook by advanced undergraduate and graduate students. It is also of interest to researchers, engineers and managers who study or practise reliability and maintenance. 

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