Stochastic Processes Stochastic Processes

Stochastic Processes

with Applications to Reliability Theory

    • USD 119.99
    • USD 119.99

Descripción editorial

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, andthe 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. 

GÉNERO
Técnicos y profesionales
PUBLICADO
2011
27 de mayo
IDIOMA
EN
Inglés
EXTENSIÓN
264
Páginas
EDITORIAL
Springer London
VENTAS
Springer Nature B.V.
TAMAÑO
5.8
MB

Más libros de Toshio Nakagawa

Which-Is-Better (WIB): Problems in Reliability Theory Which-Is-Better (WIB): Problems in Reliability Theory
2023
Optimal Inspection Models with Their Applications Optimal Inspection Models with Their Applications
2023
Advanced Maintenance Policies for Shock and Damage Models Advanced Maintenance Policies for Shock and Damage Models
2017
Maintenance Overtime Policies in Reliability Theory Maintenance Overtime Policies in Reliability Theory
2015
Random Maintenance Policies Random Maintenance Policies
2014
Stochastic Reliability and Maintenance Modeling Stochastic Reliability and Maintenance Modeling
2013