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Informatique et Mathématiques appliquées
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> Formation > Cursus ingénieur

RANDOM PROCESSES

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  • Number of hours

    • Lectures : 18.0
    • Tutorials : 18.0
    ECTS : 3.0

Goals

This course is a concise introduction to random processes with modelling and simulation in mind. We will describe and study some basic tools that permit to model time/space random phenomena. It deals with key ingredients involved in modelization and decision theory hand in hand with statistical and operational research techniques. Last but not least, stochastic modelling spreads in a wide range of field such as (non exhaustive list) image processing, biology, physics etc...


Contact Pierre ETORE

Content

1.Markov chains; 2.Renewal processes; 3.Poisson process; 4.Jump Markov processes; 5.Queues.



Prerequisites

Probability theory and Applications 1.

Some knowledge in the topics of Probability theory and Applications 2 will facilitate.

Tests

Continuous assesment (CC) ; written final test (E).



N1 = 1/3 *CC +2/3*E1
<br>
N2= 1/3*CC+2/3*E2

Additional Information

Curriculum->MMIS.->Semester 3

Bibliography

Durrett, R. “Essential of Stochastic processes”, Springer Verlag, New York, 1999.
Ferrari, P. A., Galves, A. “Coupling and regeneration for stochastic processes” téléchargeable à http://www.ime.usp.br/~pablo/book/oct2001/oct2001.pdf
Grimmett, G., Stirzaker, D. “Probability and Random Processes”, Oxford 3 edition 2001

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Université Grenoble Alpes