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Frequency Analysis (3 cr)

Code: ELA22GY15-3001

General information


Enrollment

30.11.2023 - 07.01.2024

Timing

15.01.2024 - 17.03.2024

Number of ECTS credits allocated

3 op

Mode of delivery

Contact teaching

Unit

Faculty of Technology and Seafaring

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

  • ELA22-A (Size: 30. Open UAS: 0.)
  • ELA22-E (Size: 30. Open UAS: 0.)
  • ELA22-K (Size: 30. Open UAS: 0.)
  • ELA22-I (Size: 30. Open UAS: 0.)

Groups

  • ELA22D-V
    Ingenjör (YH), el- och automationsteknik, 2022, dagstudier

Small groups

  • ELA22-A
  • ELA22-E
  • ELA22-K
  • ELA22-I

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

Location and time

15.1.2024, W33

Materials

Lecture notes
Web-based material

Teaching methods

Lectures
Exercises
Self studies

Student workload

Totally 81 hours, of which 36 hours as classroom education.

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.

Assessment methods and criteria

Examination is based on an individual exam and assignments.
A minimum of points in the exam is required to pass the course.

Assessment criteria, fail (0)

Less than 10 points in the exam.

Assessment criteria, satisfactory (1-2)

At least 10 points in the exam.

Assessment criteria, good (3-4)

At least 16 points in the exam.

Assessment criteria, excellent (5)

At least 22 points in the exam.

Qualifications

No prerequisites