ET1554 - Signal Processing - Blekinge Institute of Technology

1. Descision

This course is established by Dean 2022-04-01. The course syllabus is approved by Head of Department of Mathematics and Natural Science 2026-04-01 and applies from 2026-04-01.

2. Entry requirements

Admission to the course requires taken course Theory of transforms, 6 credits.

3. Objective and content

3.1 Objective

The aim of the course is for the student to acquire basic knowledge in signal processing and systems theory with the intention of providing the necessary mathematical tools for analysis and processing of measured signals.

3.2 Content

Central elements of the course are:

Basic definitions

Discrete time signals
Frequency concept

Linear time-invariant systems

Time-discrete signals and systems
Connection between input and output signals

Frequency analysis and transformers

Fourier series and Fourier transforms of discrete time signals
Parseval's relation
Linear time-invariant systems and their frequency properties
Signals and their frequency content

Sampling and reconstruction

Sampling of time-continuous signals
Sampling theorem, folding and reconstruction
A/D and D/A conversion

Discrete fouriertransform (DFT)

Frequency Plane Sampling
Discrete Fourier transform (DFT) and its applications

4. Learning outcomes

The following learning outcomes are examined in the course:

4.1. Knowledge and understanding

demonstrate knowledge and understanding of basic signal processing definitions
demonstrate knowledge and understanding of basic properties of linear systems.
demonstrate basic knowledge and understanding of Fourier series, Fourier transform and discrete Fourier transform.
demonstrate basic knowledge and understanding of the sampling process of time-continuous signals.

4.2. Competence and skills

use basic signal processing definitions. use different properties of linear systems.
use discrete Fourier series, Fourier transform.
apply the sampling process of time-continuous signals.

4.3. Judgement and approach

create an approach and practical skills in basic signal processing.

5. Learning activities

The teaching consists of lectures, calculation exercises, assignments and laboratory work.

6. Assessment and grading

Modes of examinations of the course

Code	Module	Credit	Grade
2210	On-campus Examination[1]	4 credits	AF
2220	Laboratory Session 1	0.7 credits	GU
2230	Laboratory Session 2	0.8 credits	GU
2240	Written assignment 1	1 credits	GU
2250	Written assignment 2	1 credits	GU

[1] Determines the final grade for the course, which will only be issued when all components have been approved.

The course will be graded A Excellent, B Very good, C Good, D Satisfactory, E Sufficient, FX Failed result, a little more work required, F Fail.

The examiner may carry out oral follow-up of written examinations.

The information before the start of the course states the assessment criteria and make explicit in which modes of examination that the learning outcomes are assessed.

An examiner can, after consulting the Disability Advisor at BTH, decide on a customized examination form for a student with a long-term disability to be provided with an examination equivalent to one given to a student who is not disabled.

7. Course evaluation

The course evaluation should be carried out in line with BTH:s course evaluation template and process.

8. Restrictions regarding degree

The course can form part of a degree but not together with another course the content of which completely or partly corresponds with the contents of this course.

9. Course literature and other materials of instruction

Proakis, J.G. & Manolakis D.G. (2013). Digital Signal Processing. (4th Edition)Prentice-Hall.
ISBN 9781292025735

10. Additional information

This course replaces ET1539

Course syllabus