course-details-portlet

AIS2201 - Signal Processing

About

Examination arrangement

Examination arrangement: Portfolio assessment
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
Portfolio assessment 100/100

Course content

The course contains a selection of the following topics:

  • Fundamental properties of analog signals in time and frequency domain
  • Sampling: discrete-time signals, Nyquist sampling theorem, aliasing, basic quantization
  • Frequency analysis: Fourier transform in various forms, spectral leakage, window functions
  • Digital LTI systems: LTI criteria, difference equation, impulse response, convolution
  • FIR filters: Frequency response and basic design methods
  • IIR filters: z-transform, pole-zero maps, stability, and basic design methods
  • Implementation of digital filters
  • Possibly other topics

More details on the curriculum will provided during the start of semester.

Learning outcome

Knowledge

  • The candidate can explain basic properties of discrete-time signals and the connection between representations in the time domain and the frequency domain.
  • The candidate can explain the properties of LTI systems and how signals are affected in an LTI system.
  • The candidate can explain how digital programming tools can be used for modelling and processing in signal analysis.

Skills

  • The candidate can perform basic signal analysis in time and frequency domain with the use of programming tools, and can explain the connection between the two domains.
  • The candidate can use programming tools for analysis of digital LTI systems.
  • The candidate can calculate the output signal from a simple LTI system.
  • The candidate can implement digital filters in a practical setting.

General competence

  • The candidate can apply knowledge about signals and systems and their connection to a variety of domains.
  • The candidate appreciates and can discuss the overall limitations in systems composed of subsystems from a signals and systems perspective.

Learning methods and activities

Learning activities generally include a mix of lectures, tutorials and practical lab/project work. A constructivist approach for learning is endorsed, with focus on problem solving and practical application of theory.

Compulsory assignments

  • A selection of learning activities must be approved

Further on evaluation

The final grade is based on an overall evaluation of the portfolio, which consists of a number of works delivered through the semester. The portfolio contains assignments that are carried out, digitally documented and submitted during the term. Both individual and team assignments may be given. Assignments are designed to help students achieve specific course learning outcomes, and formative feedback is given during the period of the portfolio. The re-sit exam is an oral exam the following spring.

Specific conditions

Admission to a programme of study is required:
Automation and Intelligent Systems - Engineering (BIAIS)

Required previous knowledge

The course has no prerequisites.

It is a requirement that students are enrolled in the study programme to which the course belongs.

Course materials

An updated course overview, including curriculum, is presented at the start of the semester and will typically also include English material.

Credit reductions

Course code Reduction From To
IELEA2302 7.5 AUTUMN 2023
IE203412 7.5 AUTUMN 2023
More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Third-year courses, level III

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2024

Language of instruction: English, Norwegian

Location: Ålesund

Subject area(s)
  • Signal Processing
  • Engineering Cybernetics
  • Engineering
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of ICT and Natural Sciences

Timetable

List view
Calendar view

Examination

Examination arrangement: Portfolio assessment

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD Portfolio assessment 100/100

Release
2024-12-02

Submission
2024-12-09


09:00


12:00

INSPERA
Room Building Number of candidates

Examination arrangement: Oral Examination

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring UTS Oral Examination 100/100
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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