Course syllabus

Optimal och adaptiv signalbehandling
Optimum and Adaptive Signal Processing

EITN60, 7,5 credits, A (Second Cycle)

Valid for: 2023/24
Faculty: Faculty of Engineering, LTH
Decided by: PLED BME
Date of Decision: 2023-04-13

General Information

Elective for: BME4-sbh, C4, D4-ssr, E4-ss, E4-bg, F5, F5-ss, MSOC2, MWIR2, Pi4-ssr
Language of instruction: The course will be given in 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.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

Competences and skills
For a passing grade the student must

Judgement and approach
For a passing grade the student must


Optimum filtering



Basics about adaptive filters

The LMS family

The RLS family

Examination details

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: The grade is based on the exam in the end of the course.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Code: 0119. Name: Written Exam.
Credits: 6. Grading scale: TH. Assessment: Written Examination.
Code: 0219. Name: Project.
Credits: 1,5. Grading scale: UG. Assessment: Project Report.


Assumed prior knowledge: EITF75 Digital signal processing OR EITA50 Signal processing in multimedia OR EITF15, BMEF25 Digital signal processing - theory and applications OR BMEA05 Signals and systems OR EITG10 Systems, Signals and Discrete Transforms
The number of participants is limited to: No
The course overlaps following course/s: ETTN05, ETT042

Reading list

Contact and other information

Course coordinator: Frida Sandberg,
Course coordinator: Martin Stridh,
Course homepage:
Further information: Exercises 14 h, computer exercises 14 h and laboratory work 2 x 4 h. The course might be given in English. With less than 16 participants, the course may be given with reduced teaching and more self studies.