Stochastic Processes : with Applications to Reliability Theory

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 in...

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المؤلف الرئيسي: Nakagawa, Toshio, 1942-
التنسيق: Livre numérique
اللغة:Anglais
منشور في: London : Springer London [20..].
Cham : Springer Nature
الطبعة:1st ed. 2011.
سلاسل:Springer Series in Reliability Engineering
الوصول للمادة أونلاين:Accès sur la plateforme de l'éditeur
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Accès Université d'Orléans
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ملاحظة: Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• Stochastic processes with applications to reliability theory, Toshio Nakagawa, 2011, London, Springer, 1 vol. (IX-251 p.), Springer series in reliability engineering, 978-0-85729-273-5
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245 1 0 |a Stochastic Processes :  |b with Applications to Reliability Theory   |c by Toshio Nakagawa. 
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505 1 |a 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 
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506 |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 
520 |a 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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