Course syllabus for Stochastic processes

The course syllabus contains changes
See changes

Course syllabus adopted 2020-03-12 by Head of Programme (or corresponding).

Overview

  • Swedish nameStokastiska processer
  • CodeMVE330
  • Credits7.5 Credits
  • OwnerMPENM
  • Education cycleSecond-cycle
  • Main field of studyMathematics
  • DepartmentMATHEMATICAL SCIENCES
  • GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail

Course round 1

The course round is cancelled. This course round is planned to be given every other year. For further questions, please contact the director of studies
  • Teaching language English
  • Application code 20144
  • Open for exchange studentsNo

Credit distribution

0109 Examination 7.5 c
Grading: TH		 7.5 c
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In programmes

Examiner

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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.

The course syllabus contains changes

  • Changes to course rounds:
    • 2020-03-12: Examinator Examinator changed from Michael Björklund (micbjo) to Jakob Björnberg (jakobbj) by Viceprefekt
      [Course round 1]
    • 2020-03-12: Cancelled Changed to cancelled by UOL
      [Course round 1] Cancelled