The course provides basic theory of and practical examples in media signal processing, with a special focus on media production, and sound and music computing.
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Content and learning outcomes
The course gives an introduction to signal processing in media technology with a focus on media production and sound and music computing. Examples are provided through existing applications, for example compression of sound and images or manipulation of media content by means of digital filters. The course introduces basic concepts with one-dimensional signals for example speech and music and expands these concepts to multi-dimensional data such as images and video.
Properties for discrete time signals and systems and basic signal manipulations are introduced. These manipulations use finite and infinite impulse response filters. The required signal manipulations are introduced (e g discrete Fourier transform, z-transform), as well as related mathematical operations (e.g convolution, correlation).
The theoretical background will be strongly attuned to practical and laboratory components in lectures and online exercises to relate theory to practical applications in industry.
Intended learning outcomes
Having passed the course, the student should be able to
- account for the basic mathematical properties in digital media signals
- explain and apply frequency domain transforms
- implement and modify digital filters with finite (FIR) and infinite (IIR) impulse response and apply them to media signals
- explain and compare compression algorithms for media signals
- recommend appropriate signal processing methods for different areas of media production
- modify and adapt media applications that use signal processing
in order to
- be able to adapt, integrate and evaluate signal processing methods in media production and application development.
Literature and preparations
Completed at least two courses equivalent to SF1625 Calculus in one variable, SF1624 Algebra and Geometry, DD1318 Programming technique, technical calculations and SF1626 Multivariable analysis.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
- LAB1 - Laboratory work, 4.5 credits, grading scale: P, F
- TEN1 - Written exam, 3.0 credits, grading scale: A, B, C, D, E, FX, 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.
Opportunity to complete the requirements via supplementary examination
Opportunity to raise an approved grade via renewed examination
- 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 about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.Course web DM1135
Main field of study
In this course, the EECS code of honor applies, see: