Stationary Stochastic Processes
5 credits
Syllabus, Master's level, 1MS025
This course has been discontinued.
A revised version of the syllabus is available.
- Code
- 1MS025
- Education cycle
- Second cycle
- Main field(s) of study and in-depth level
- Mathematics A1N
- Grading system
- Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Finalised by
- The Faculty Board of Science and Technology, 6 May 2013
- Responsible department
- Department of Mathematics
Entry requirements
120 credits in Science and Technology including Probability and Statistics
Learning outcomes
On completion of the course, the student should be able to:
- perform calculations with expectations and covariances in stationary processes;
- calculate relationship between covariance properties in the time domain and spectral properties in the frequency domain;
- carry out calculations with linear filters (AR and MA);
- perform simple inference for stationary processes for example estimation of spectrum, filtering;
- suggest appropriate stochastic models of processes that appear in technical applications and carry out prediction.
Content
stationary processes (introduction, definitions); the spectral description; normal processes; filtering (linear systems, filter and cross spectrum); inference for stationary processes; applications (filtering; prediction). advanced case studies where the course content is applied on problems from technology or natural sciences.
Instruction
Lectures, problem-solving sessions, possibly laboratory sessions. Guest lecture.
Assessment
Assignments (4.5 credits) and computer lab (0.5 credits)