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Applied Stochastic Processes
Last Updated: 2026-02-05 15:18:44
Abstract
Poisson Processes, Renewal Processes, Markov Processes and some of their generalisations (Semi-Markov, Markov-Renewal, etc.), Queueing Models, Branching Processes, Brownian Motion. We will discuss various examples coming from diverse fields of application.
Objective
The theory of Stochastic Processes concerns the modelling of random phenomena in time. In this course we will give an introduction to this theory with as main emphasis applications. Specific topics treated include: Poisson Processes, Renewal Processes, Markov Processes and Brownial Motion.
Content
Poisson Processes, Renewal Processes, Markov Processes and some of their generalisations (Semi-Markov, Markov-Renewal, etc.), Queueing Models, Branching Processes, Brownian Motion. We will discuss various examples coming from diverse fields of application.
Resources
Literature
G.R. Grimmett and D.R. Stirzaker: Probability and Random Processes (Sec.Ed.), Oxford UP (1992). S.Karlin and H.M. Taylor: A First Course in Stochastic Processes (Sec.Ed.), Academic Press (1975), A Second Course in Stochastic Processes, Academic Press (1981). S.I. Resnick: Adventures in Stochastic Processes, Birkhaeuser (1992). A.M. Ross: Stochastic Processes, Wiley (1983).
General Information
- Language
- English
- Levels
- BSC , MSC
- Frequency
- Every two years
Examination
- Type
- session examination
- Mode
- oral 30 minutes
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Applied Stochastic Processes |
|
3 h weekly |
| exercise | Applied Stochastic Processes |
|
1 h weekly |