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Syllabus for

Academic year
MVE330 - Stochastic processes  
Stokastiska processer
 
Syllabus adopted 2020-03-12 by Head of Programme (or corresponding)
Owner: MPENM
7,5 Credits
Grading: TH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Education cycle: Second-cycle
Major subject: Mathematics
Department: 11 - MATHEMATICAL SCIENCES

The course round is cancelled. For further questions, please contact the director of studies MPENM: ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, contact information can be found here. This course round is planned to be given every other year.


Teaching language: English
Application code: 20144
Open for exchange students: No

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0109 Examination 7,5 c Grading: TH   7,5 c   Contact examiner

In programs

MPENM ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 2 (elective)

Examiner:

Jakob Björnberg

  Go to Course Homepage


Eligibility

General entry requirements for Master's level (second cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

English 6 (or by other approved means with the equivalent proficiency level)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Course specific prerequisites

One of the courses:

MVE140 Foundations of probability theory

TMS110 Markov theory

MVE170 Basic Stochastic Processes

TMS125 Basic Stochastic Processes F

MVE135 Random Processes with Applications

Or a similar background: Contact the examinator for more information.

Aim

The course gives a solid knowledge of stochastic processes, intended to
be sufficient for applications in mathematical sciences as well as
natural sciences, at all levels. An advanced treatment of the theory of
stochastic processes relies on probability theory and mathematical
analysis. The purpose of the course is to give such a treatment. This
means that there is a certain focus on proofs and rigor.

Learning outcomes (after completion of the course the student should be able to)

The course gives a solid knowledge of stochastic processes, intended to be
sufficient for applications in mathematical sciences as well as natural
sciences, at all levels. An advanced treatment of stochastic processes
relies on probability theory and mathematical analysis. The purpose of the
course is to give such a treatment. This means that there is a certain
focus on proofs and rigour.

Content

Stationarity and weak stationarity. Gaussian processes. Renewal theory and queues.Martingales.

Organisation

Lectures. Reading assignments.

Literature

Grimmett G. and Stirzaker D.: Probability and Random Processes, Third
Edition 2001. Chapters 6 and 8-12.

Examination including compulsory elements

Home assignments and/or a written final exam.


Page manager Published: Mon 28 Nov 2016.