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DT1120 Spectral Transforms 6.0 credits

Information per course offering

Course offerings are missing for current or upcoming semesters.

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus DT1120 (Autumn 2008–)
Headings with content from the Course syllabus DT1120 (Autumn 2008–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Oscillations and complex phasors. Time-discrete signals, quantization and sampling. Linear systems, digital filters with and without feedback. Impulse response and step response. Magnitude response and transfer function. Convolution. Periodic signals and fourier series. Discrete fourier transform, FFT. Spectrum and spectrogram. Windowing. Source-filter models. Formants and fundamental frequency. Filtering, convolution and transforms in two dimensions. Discrete cosine transform. Image compression.

Intended learning outcomes

The student should after the course be able to

  • analyse audio signals using spectrum/spectrogram and explain relations between spectrum, analysis window length, analysis bandwidth and resolution in time and frequency domains
  • explain and calculate the consequences of sampling and quantisation of analogue signals
  • express signals mathematically in terms of complex phasors, and utilise fourier series to describe periodic signals
  • analyse simple linear systems, and calculate various properties of theese such as filter equation, transfer function, pole- and zero configuration, magnitude response and impulse response (and for two pole resonators also center frequency and bandwidth) and relate these to each other.
  • explain and apply convolution of signals in one and two dimensions.
  • explain function and scope of use, and numerically compute the discrete fourier transform, and state the basic principle and computational properties of the FFT algorithm.
  • Account for basic principles and algorithms used in filtering and spectrally based compression of images
  • Implement filtering and spectral treatment of actual signals (sounds/images) using Matlab

Literature and preparations

Specific prerequisites

No information inserted

Literature

To be announced at the web page for the course at least 2 weeks before the start of the course.

Examination and completion

Grading scale

A, B, C, D, E, FX, F

Examination

  • TEN1 - Examination, 4.5 credits, grading scale: A, B, C, D, E, FX, F
  • LAB1 - Laboratory Work, 1.5 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

If the course is discontinued, students may request to be examined during the following two academic years.

Other requirements for final grade

One written examination (4,5 university credits) and a laboratory course (1,5 university credits).

Examiner

No information inserted

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Technology

Education cycle

First cycle