Signal/Data Processing Systems


Content, progress and pedagogy of the module

Learning objectives


• must have knowledge about compression of one and two dimensional signal/data representations
• must have knowledge about classical and Baysian statistical methods for processing of noisy signals
• must have knowledge about simulation techniques and in particular about Markov chain and Monte Carlo methods
• must have knowledge about how sparse representations and statistical techniques influences real-world data/signals


• must be able to use Baysian and hierarchical statistical methods to analyse time series and lattice data and to evaluate the validity of the results obtained
• must be able to use compressed signal/data representations on real or synthetic data and be able to evaluate the quality of the signal/data reconstruction


• are able to communicate results of statistical analyses to non-specialists within advanced signal processing
• are able to independently develop statistical models suitable for analysis of real-world signals such as noisy digital images or communication signals
• are able to use sparse representations and/or statistical methods to solve a given practical problem and, if needed, make minor adjustments to the methods to obtain the wanted functionality

Type of instruction

Projekt work including PBL elements.

Extent and expected workload

This is a 15 ECTS project module and the work load is expected to be 412,5 hours for the student.



Name of examSignal/Data Processing Systems
Type of exam
Oral exam based on a project
Permitted aids
All written and all electronic aids
Assessment7-point grading scale
Type of gradingExternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleSignal/databehandlende systemer
Module codeK-MTK2-PRO15
Module typeProject
Duration1 semester
Language of instructionDanish
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module


Study BoardStudy Board of Mathematical Sciences
DepartmentDepartment of Mathematical Sciences
FacultyFaculty of Engineering and Science