389.040 Signal Detection
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023S, VO, 2.0h, 3.0EC


  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VO Lecture
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to formulate hypotheses test, to develop analytical solutions, to characterize the performance of these solutions qualitatively and quantitatively, and to apply these capabilities to real-world engineering problems.

Subject of course

  • Introduction: motivation, historical remarks, classification of decision problems, performance metrics
  • Simple hypothesis tests: Bayesian detector, MAP and ML detector, Neyman-Pearson detector, minimax detector
  • Detection of known signals in Gaussian noise: correlator, matched filter
  • Detection of Gaussian signals in Gaussian noise: estimator-correlator, canonical implementation
  • Composite hypothesis tests: Bayesian detector, uniformly most powerful detector, locally optimal detector, invariant detectors, generalized likelihood-ratio detector
  • Detection of deterministic signals with unknown parameters: subspace detector, CFAR detector

Teaching methods

Conventional lectures on the blackboard supported by electronic media.

Mode of examination


Additional information

The lecture is given every Monday at 1:00pm in Sem. 389 (CG0118).

First class: March 6, 2023 at 1pm



Course dates

Mon13:00 - 15:0006.03.2023 - 26.06.2023Sem 389 Vorlesung
Signal Detection - Single appointments
Mon06.03.202313:00 - 15:00Sem 389 Vorlesung
Mon13.03.202313:00 - 15:00Sem 389 Vorlesung
Mon20.03.202313:00 - 15:00Sem 389 Vorlesung
Mon27.03.202313:00 - 15:00Sem 389 Vorlesung
Mon17.04.202313:00 - 15:00Sem 389 Vorlesung
Mon24.04.202313:00 - 15:00Sem 389 Vorlesung
Mon08.05.202313:00 - 15:00Sem 389 Vorlesung
Mon15.05.202313:00 - 15:00Sem 389 Vorlesung
Mon22.05.202313:00 - 15:00Sem 389 Vorlesung
Mon05.06.202313:00 - 15:00Sem 389 Vorlesung
Mon12.06.202313:00 - 15:00Sem 389 Vorlesung
Mon19.06.202313:00 - 15:00Sem 389 Vorlesung
Mon26.06.202313:00 - 15:00Sem 389 Vorlesung

Examination modalities

oral exam

Course registration

Not necessary


Study CodeObligationSemesterPrecon.Info
066 460 Physical Energy and Measurement Engineering Mandatory elective
066 507 Telecommunications Not specified
710 FW Elective Courses - Electrical Engineering Elective


Lecture notes for this course are available.

Further References

  • Stephen M. Kay, "Fundamentals of Statistical Signal Processing: Detection Theory," Prentice-Hall: 1998.
  • H. Vincent Poor, "An Introduction to Signal Detection and Estimation," Springer: 1988.
  • Louis L. Scharf, "Statistical Signal Processing," Addison-Wesley: 1991.

Previous knowledge

probability, random variables, stochastic processes, linear algebra (on the level of the courses "Signal Processing 1" und "Signal Processing 2")