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Ph.D. Level Courses

Detection and Estimation Theory


This course gives a comprehensive introduction to estimation and detection (decision-making) based on observations of discrete-time and continuous-time signals. The course has applications in many areas, for example communications and radar.


Prof. Prof. Erik G. Larsson, ISY/Communication Systems


The course is open to students enrolled in a Ph.D. program at Linkoping University/ISY. External participants upon request. If you have interest to participate, please register by sending an email to the instructor, by Jan 31, 2010.


Good knowledge of linear algebra, probability, and stochastic processes. General mathematical maturity.

Course outline (tentative)

  • Binary and M-ary hypothesis testing
  • Detection theory: Neyman-Pearson, ROC, Bayesian criteria
  • Estimation theory: classical estimation, maximum likelihood, Cramer-Rao lower bound, Bayesian estimation, MMSE
  • Composite hypothesis testing, model order selection
  • General Gaussian models
  • Representation of continuous-time waveforms and noise (Karhunen-Loeve expansion)
  • Detection and parameter estimation of signals in additive Gaussian noise


The course consists of 12 seminars/meetings. Course start Monday February 15, 2010, at 9.15 am (room: Hammingrummet).

A course schedule (with reading and homework) can be found here (this will be continuously updated during the course).


  • H. van Trees, "Detection, estimation and modulation theory", Wiley, 1967. (Paperback edition ISBN 0-471-095176, 2001.)
  • Course notes (will be continuously updated during the course) are here
  • Additional homework problems are here
  • Supplementary material handed out during the course and/or available from this webpage


The course is estimated to be worth 10 ECTS credits.


  • 5 ECTS version:
    • Active seminar participation.
    • Solve 40% of the problems for each homework assignment.
    • Oral exam, when necessary.
  • 10 ECTS version:
    • Active seminar participation
    • Solve 75% of the problems for each homework assignment.
    • Present one or more problem per homework seminar on the board.
    • Oral exam, when necessary.
Homework to be solved, written up and submitted individually. Deadlines to be strictly observed.

Page responsible: Erik Larsson
Last updated: 2019 07 29   15:48