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.

2019S, VO, 2.0h, 3.0EC


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

Aim of course

  • knowledge about fundamental concepts and methods of signal detection
  • ability to formulate and solve practical detection problems
  • improvement of technical english

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

Additional information

Place: SEM 389 (room no. CG0118), Institute of Telecommunications

Date: Monday, 1:30-3:00 pm; first class: Monday, March 4, 2019



Course dates

Mon13:00 - 15:0004.03.2019 - 24.06.2019Sem 389 Vorlesung
Mon12:00 - 14:0003.06.2019Sem 389 Vorlesung
Signal Detection - Single appointments
Mon04.03.201913:00 - 15:00Sem 389 Vorlesung
Mon11.03.201913:00 - 15:00Sem 389 Vorlesung
Mon18.03.201913:00 - 15:00Sem 389 Vorlesung
Mon25.03.201913:00 - 15:00Sem 389 Vorlesung
Mon01.04.201913:00 - 15:00Sem 389 Vorlesung
Mon08.04.201913:00 - 15:00Sem 389 Vorlesung
Mon29.04.201913:00 - 15:00Sem 389 Vorlesung
Mon06.05.201913:00 - 15:00Sem 389 Vorlesung
Mon13.05.201913:00 - 15:00Sem 389 Vorlesung
Mon20.05.201913:00 - 15:00Sem 389 Vorlesung
Mon27.05.201913:00 - 15:00Sem 389 Vorlesung
Mon03.06.201912:00 - 14:00Sem 389 Vorlesung
Mon17.06.201913:00 - 15:00Sem 389 Vorlesung
Mon24.06.201913:00 - 15:00Sem 389 Vorlesung

Examination modalities

oral exam

Course registration

Not necessary



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")