Scheda programma d'esame
METODI NUMERICI PER CATENE DI MARKOV
BEATRICE MEINI
Anno accademico2016/17
CdSMATEMATICA
Codice148AA
CFU6
PeriodoPrimo semestre
LinguaItaliano

ModuliSettoreTipoOreDocente/i
METODI NUMERICI PER CATENE DI MARKOV/aMAT/08LEZIONI42
BEATRICE MEINI unimap
Programma non disponibile nella lingua selezionata
Learning outcomes
Knowledge
The student who successfully completes the course will have the ability to to know computational and applicative issues related to Markov chains and queueing theory. In particular, he/she will be able to apply advanced algorithms for the efficient numerical solution of Markov chains
Assessment criteria of knowledge
With the oral presentation, to be made to the teacher and possibly the other students, the student must demonstrate the ability to approach a circumscribed research problem, and organise an effective exposition of the results.

Methods:

  • Final oral exam
  • Final essay

Further information:
seminar presentation 80% approach to a research problem 20%

Teaching methods

Delivery: face to face

Learning activities:

  • attending lectures
  • participation in seminar
  • individual study
  • Laboratory work

Attendance: Advised

Teaching methods:

  • Lectures
  • Seminar
  • laboratory

Syllabus
Introduction to Markov chains and related computational problems. Theory of nonnegative matrices. Numerical methods for finite Markov chains. Markov chains of M/G/1 type. Numerical methods for infinite structured Markov chains, like M/G/1-type, Quasi-birth and death processes.
Bibliography
Recommended reading includes the following books: D.A. Bini, G. Latouche, B. Meini, Numerical Methods for Structured Markov Chains, Oxford University Press 2005; G. Latouche, V. Ramaswami, Introduction to Matrix Analytic Methods in Stochastic Modeling, SIAM 1999; W.J. Stewart, Introduction to the Numerical Solution of Markov Chains. Princeton University Press, 1994.
Ultimo aggiornamento 14/11/2016 17:27