Course Syllabus for

Detection Theory

EIT165F, 9 credits

Valid from: Autumn 2017
Decided by: Professor Thomas Johansson
Date of establishment: 2017-12-07

General Information

Division: Electrical and Information Technology
Course type: Third-cycle course
Teaching language: English


The course aims to provide a deep understanding of the subject Detection Theory. Detection theory can be applied to many different fields, and within communication theory it plays a central role. The department’s research is dominated by different aspects of communication. To have a solid basis and skills in detection is of fundamental importance for a large fraction of LTH’s doctoral students. The course provides them with a solid scientific basis for communication theory


Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must

Judgement and Approach

For a passing grade the doctoral student must have the ability to independently acquire important information from an extensive text, such as a textbook

Course Contents

The Neyman-Pearson Theorem, Bayes Risk, Matched and generalized matched filters, Estimator-Correlator structures, Generalized likelihood tests, LMP detectores, detection of signals with unknown parameters, non-Gaussian noise, detection of model changes

Course Literature

Kay, Steven M.: Detection Theory. Prentice Hall, 1993..

Instruction Details

Types of instruction: Lectures, seminars

Examination Details

Examination format: Written assignments
Grading scale: Failed, pass

Admission Details

Further Information

Course Coordinator: Fredrik Rusek

Course Occasion Information

Contact and Other Information

Course coordinators:
Web page:

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