Signal processing
About the course
The course is available as a singular course. The course is also available to exchange students and Fulbright students.
The course outlines the fundamental importance of sinusoids, in the form of complex exponential functions, as building blocks of signals, and provides an introduction to frequency (spectrum) analysis. Sampling and aliasing is covered, and the processing of discrete signals using FIR and IIR filters both in the time (impulse response), frequency (system function) and Z-domain is explained. The continuous-time Fourier transform is introduced, with applications in amplitude modulation and sampling, leading to the definition of the discrete Fourier transforms (DFT and FFT). Exercises are emphasized. Practical signal processing using programming is also emphasized, hence basic programming skills are advantageous.
Admission requirements
Admission requirements are generell studiekompetanse + SIVING. (matematikk R1 (eller matematikk S1 og S2) og R2 og fysikk 1).
Local admission, application code 9391 - singular courses in engineering sciences. The course is also available to exchange students and Fulbright students.
Objectives of the course
Knowledge - The student can
- define the role of sinusoids in signals, e.g. for synthesizing music
- describe the process of sampling and discretization of signals
- define properties of different systems for processing signals
- explain the complementary properties of time and frequency analysis
- understand the Fourier transform of signals and its use
Skills - The student can
- determine the correct sampling frequency for signal discretization
- implement signal processing solutions in Python - process discrete signals using FIR and IIR systems
- design filters for noise removal
- analyze and design processing systems both in terms of time and frequency
- use the Fourier-transform of a signal for frequency analysis and processing
General competence - The student can
- appreciate the importance of signal processing in a society with signals everywhere
- work with signal processing for data analysis
- program scripts and functions in Python
Prerequisites
Recommended prerequisites
MAT-1003 Calculus 3, MAT-1004 Linear algebra
Credit reduction
If you pass the examination in this course, you will get an reduction in credits (as stated below), if you previously have passed the following courses:
- FYS-260 Signal analysis (introduction) 9 stp
Teaching methods
Language of instruction and examination
The language of instruction is English and all of the syllabus material is in English. Examination questions will be given in English, but may be answered either in English or a Scandinavian language.Application deadline
Information to incoming exchange students
Examination
| School exam | Date: 02.12.2022 09:00 Duration: 4 Hours Weighting: 7/10 |
Grade: A–E, fail F |
| Off campus exam | Hand in: 04.11.2022 14:00 Duration: 2 Weeks Weighting: 3/10 |
Grade: A–E, fail F |
To take an examination, the student must have passed the following coursework requirements
| Programming assignment 1 | Grade: Approved – not approved |
| Programming assignment 2 | Grade: Approved – not approved |
Everything you need to know about before, during, and after the exam; registration, absence, appeals, and diplomas: UiT Exams homepage
