Course Syllabus for

Estimation Theory

EIT060F, 9 credits

Valid from: Spring 2015
Decided by: FN1/Anders Gustafsson
Date of establishment: 2015-03-15

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 Estimation Theory. Estimation 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 estimation is of fundamental importance for a large fraction of LTH’s doctoral students. The course provides them with a solid scientific basis for communiation 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

Minimum variance estimators, Cramer-Rao’s bound, optimal unbiased estimators, Maximum-likelihood estimation, least squares method, method of moments, Bayesian estimators, linear Bayesian estimators, Kalman filters

Course Literature

Kay, Steven M.: Estimation 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:

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