Course Syllabus for

Optimum and Adaptive Signal Processing
Optimal och adaptiv signalbehandling

BMEN15F, 7.5 credits

Valid from: Autumn 2018
Decided by: Professor Thomas Johansson
Date of establishment: 2018-10-08

General Information

Division: Biomedical Engineering
Course type: Course given jointly for second and third cycle
The course is also given at second-cycle level with course code: EITN60
Teaching language: English


The course provides basic knowledge in statistical signal processing and the theory of optimal methods and how they can be applied. The course presents signal processing methodology and solutions to problems where digital systems tune in automatically and adapt to the environment. The student is given enough theoretical and practical knowledge to independently be able to formulate the mathematical problem, solve it and implement the solution for use with real-life signals.


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

Course Contents

Optimum filtering -Wiener filters -Linear prediciton -The Levinson-Durbin algorithm Basics about adaptive filters -From optimal to adaptive filters -Cost functions, minimization problems and iterative procedures -Convergence and tracking capability, implementation aspects -Strategies for how to connect adaptive filters The LMS family -Principle and derivation -Convergence analysis and parameter settings -Variants including Normalized LMS, Leaky LMS, Fast LMS and Sign LMS -Matlab implementation -LMS in fixed-point arithmetic -Principle and derivation -Parameter settings The RLS family -Aspects when used -Matlab implementation -Numerical properties

Course Literature

Haykin, S.: Adaptive Filter Theory. Pearson Education, 2014. ISBN 9780273764083.

Instruction Details

Types of instruction: Lectures, laboratory exercises, exercises, project. Exercises 14 h, computer exercises 14 h and laboratory work 2 x 4 h

Examination Details

Examination formats: Written exam, written report
Grading scale: Failed, pass

Admission Details

Assumed prior knowledge: ESS040, EITF75 Digital Signal Processing or ETI265, EITA50 Signal Processing in Multimedia or EITF15 Signal processing - theory and applications.

Course Occasion Information

Contact and Other Information

Course coordinator: Frida Sandberg <>
Web page:

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