Høst 2024

FYS-2006 Signal processing - 10 stp

The course is administrated by

Institutt for fysikk og teknologi

Type of course

The course is available as a singular course. The course is also available to exchange students and Fulbright students.

Course overlap

FYS-260 Signal analysis (introduction) 9 ects

Course contents

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.

Objective 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

Language of instruction

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.

Teaching methods

Lectures: 40 hours Exercises: 40 hours