Frequency Analysis (3 cr)
Code: ELA22GY15-3004
General information
Enrollment
02.12.2025 - 31.12.2025
Timing
01.01.2026 - 03.05.2026
Number of ECTS credits allocated
3 cr
Mode of delivery
Contact teaching
Campus
Vasa, Wolffskavägen 33
Teaching languages
- Svenska
Degree programmes
- Degree Programme in Electrical Engineering and Automation
Teachers
- Roger Mäntylä
Teacher in charge
Ronnie Sundsten
Scheduling groups
- ELA24-A (Size: 40. Open UAS: 0.)
- ELA24-K (Size: 40. Open UAS: 0.)
- UIT24 (Size: 40. Open UAS: 0.)
Groups
-
ELA24D-VIngenjör (YH), el- och automationsteknik, 2024, dagstudier
-
UIT24D-VIngenjör (YH), informationsteknik, 2024
Small groups
- ELA24-A
- ELA24-K
- UIT24
Objective
The student:
- understands how a signal is sampled and represented (in the time and frequency domain)
- interprets and is able to use the information in a frequency spectrum
- is able to perform frequency analysis of a given signal
- can use suitable software to do frequency analysis
Content
Different types of signals
Periodic functions and signals
Fourier series and representation of periodic signals
Sampling and the sampling theorem
Fourier transform and FFT algorithm
Frequency analysis and interpretation of FFT spectrum
Signal analysis in matlab
Materials
Material on Moodle and web-based material.
Evaluation scale
H-5
Assessment criteria, satisfactory (1)
Knows the characteristics of the frequency spectrum for a periodic signal
Knows the characteristics of the frequency spectrum for an aperiodic signal
Can interpret the results of a frequency analysis
Assessment criteria, good (3)
Can use Fourier Series conversion tables to determine the frequency spectrum of some typical signals.
Understands, on a fundamental level, the relationship between the rate of change of the signal and the frequency spectrum of the signal.
Can use a frequency analyzer.
Assessment criteria, excellent (5)
Master the integral technique to determine the fourier coefficients for periodic signals.
Master the transform technique to determine the frequency spectra of aperiodic signals.
Can use a frequency analyzer and is also familiar with the use of Matlab as a tool for frequency analysis.
Qualifications
No prerequisites