autumn 2017

## FYS-2006 Signal processing - 10 stp

Sist endret: 20.02.2018

## The course is administrated by

Faculty of Science and Technology

## Studiested

Tromsø |

Applicants from Nordic countries: 1 June for the autumn semester and 1 December for the spring semester. Applicants from outside the Nordic countries: 1 October for the spring semester and 15 April for the autumn semester.

## Type of course

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

Admission requirements are generell studiekompetanse + REALFA. Local admission, application code 9336 - singular courses in natural sciences. The course is also available to exchange students and Fulbright students.

## 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.

## Recommended prerequisites

MAT-1003 Calculus 3, MAT-1004 Linear algebra

## 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 a programming language - 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 expertise - 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

## 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

## Assessment

Portfolio assessment of a take-home examination counting about 25 % and a final 4 hour written examination counting about 75 %. All components in the portfolio are assessed as a whole and one combined grade is given. Assessment scale: Letter grades A-F.

Re-sit examination (section 22): Students having failed the last ordinary examination are offered a re-sit examination early in the following semester, if the course is compulsory in their study programme, otherwise given that an examination is already being arranged. 4 hour written examination counting 100 %.

Postponed examination (sections 17 and 21): Students with valid grounds for absence will be offered a postponed examination. Postponed take-home examination is arranged during the semester if possible, otherwise early in the following semester. Postponed written examination is held early in the following semester.

See indicated sections in Regulations for examinations at the UiT The arctic university of Norway for more information.

Coursework requirements: Access to the final examination requires submission of take-home examination.

## Date for examination

Written test 04.12.2017

The date for the exam can be changed. The final date will be announced in the StudentWeb early in May and early in November.

## Course overlap

FYS-260 Signal analysis (introduction) 9 stp