Compressive Sensing


Content, progress and pedagogy of the module

Learning objectives


  • must have knowledge of compressed (sparse) representation of signals/data in one and two dimensions
  • must have knowledge of the concepts measurement matrix and dictionary
  • must have knowledge of hardware realizations at block level, which use compressive representation of signals/data (e.g. multi-coset and random demodulator architectures)
  • must have knowledge of the relation between compressed representation and classical representation of signals/data
  • must have knowledge of key concepts and methods within compressed signal/data representation
  • must have knowledge of formulation of signal/data reconstruction as different types of optimization problems (e.g. Greedy Pursuit and Orthogonal Matching Pursuit)


  • must be able to apply compressed signal/data representation in analysis- and/or synthesis-related applications
  • must be able to simulate and assess the quality of signals/data which are represented in compressed form


  • must be able to assess when compressed signal/data representation is appropriate
  • must be able to formulate the basic elements for a given signal/data type and assess the signal/data quality in relation to the number of signal/data components

Type of instruction

Lectures with exercises.

Extent and expected workload

This is a 5 ECTS course module and the work load is expected to be 150 hours for the student.



Name of examCompressive Sensing
Type of exam
Active participation/continuous evaluation
Reexam: Written or oral examination
AssessmentPassed/Not Passed
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleKomprimeret signal-/dataanalyse og syntese
Module code23KMTK2COSE
Module typeCourse
Duration1 semester
Language of instructionDanish and English
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module


Study BoardStudy Board of Mathematical Sciences
DepartmentDepartment of Mathematical Sciences
FacultyThe Faculty of Engineering and Science