Advanced Signal Processing (ELE640)

We surround ourselves with smart phones, watches and sensors. With the help of such equipment we have conversations, listen to music, watch films, receive information about the world around us as well as monitor our surroundings and ourselves. We need advanced signal and image processing to be able to interpret and give meaning to data from such sensors, including medical equipment. This course builds on subjects such as Signal Processing, Image Processing and Computer Vision as well as Machine Learning. We learn basic theory, some new techniques and establish "building blocks", which we use in specific applications. We learn to extract features from data we can feed into machine learning programs.


Course description for study year 2024-2025. Please note that changes may occur.

Facts

Course code

ELE640

Version

1

Credits (ECTS)

10

Semester tution start

Autumn

Number of semesters

1

Exam semester

Autumn

Language of instruction

Norwegian

Offered by
Time table

View course schedule

Content

NB! This is an elective course and may be cancelled if fewer than 10 students are enrolled by August 20th for the autumn semester.

Topics covered are: Multirate signal processing, wavelets and filter banks, stochastic signal processing, quantization, techniques and methods for signal and image compression, as well as feature extraction from signals in the time and frequency domain. We will use signal and image processing in specific applications, including examples using biomedical data. We will also use machine learning to make decision systems.

Learning outcome

Knowledge:

  • The student will learn advanced signal processing techniques that build on ELE500 Signal processing and ELE510 Image processing and computer vision.
  • Students will gain knowledge about signal and image processing tools, such as multirate signal processing, wavelets and filter banks, stochastic signal processing, quantization, techniques and methods for signal and image compression, as well as feature extraction from signals in the time and frequency domain.
  • The student will understand how signal and image processing techniques can be used in specific applications such as compression of images and signals.
  • The student will also understand how signal and image processing can be used in biomedical applications.

Skills:

The students will be able to use advanced mathematical and statistical methods in the analysis and construction of signal processing systems as well as the ability to use programming tools to achieve this (Matlab and/or Python).

General competence:

After this course the student should have a general understanding of both fundamental and some advanced concepts used in signal processing, as well as an understanding in how to use such concepts in real world signal processing problems.

Required prerequisite knowledge

ELE500 Signal Processing

Recommended prerequisites

ELE510 Image Processing and Computer Vision, ELE520 Machine Learning

Exam

Coursework requirements

Assessement, Presenting the project in class

Assignments

7 out of 10 assignments must be approved by subject teacher within the specified deadlines.

Course teacher(s)

Course coordinator:

Ketil Oppedal

Head of Department:

Tom Ryen

Method of work

4-6 hours of lectures and assignment reviews per week. Assignments using Matlab and/or Python.

Open for

Admission to Single Courses at the Faculty of Science and Technology
Robot Technology and Signal Processing - Master of Science Degree Programme

Course assessment

There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital subject evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.

Literature

Search for literature in Leganto