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Autor(en): 
  • N. Limnios
  • G. Oprisan
  • Semi-Markov Processes and Reliability 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Oktober 2012  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Artificial Intelligence / C / Computational Intelligence / Industrial safety / Mathematics and Statistics / Probabilities / Probability & statistics / Probability Theory / Probability Theory and Stochastic Processes / quality control / Quality Control, Reliability, Safety and Risk / reliability / Security Science and Technology / Stochastics
    ISBN:  9781461266402 
    EAN-Code: 
    9781461266402 
    Verlag:  Springer Nature EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Statistics for Industry and Technology  
    Dimensionen:  H 254 mm / B 178 mm / D  
    Gewicht:  463 gr 
    Seiten:  222 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    At first there was the Markov property. The theory of stochastic processes, which can be considered as an exten­ sion of probability theory, allows the modeling of the evolution of systems through the time. It cannot be properly understood just as pure mathemat­ ics, separated from the body of experience and examples that have brought it to life. The theory of stochastic processes entered a period of intensive develop­ ment, which is not finished yet, when the idea of the Markov property was brought in. Not even a serious study of the renewal processes is possible without using the strong tool of Markov processes. The modern theory of Markov processes has its origins in the studies by A. A: Markov (1856-1922) of sequences of experiments "connected in a chain" and in the attempts to describe mathematically the physical phenomenon known as Brownian mo­ tion. Later, many generalizations (in fact all kinds of weakenings of the Markov property) of Markov type stochastic processes were proposed. Some of them have led to new classes of stochastic processes and useful applications. Let us mention some of them: systems with complete connections [90, 91, 45, 86]; K-dependent Markov processes [44]; semi-Markov processes, and so forth. The semi-Markov processes generalize the renewal processes as well as the Markov jump processes and have numerous applications, especially in relia­ bility.
      



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