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FEO3250 Information Theory and Source Coding 12.0 credits

About course offering

For course offering

Spring 2024 Start 16 Jan 2024 programme students

Target group

No information inserted

Part of programme

No information inserted

Periods

P3 (12.0 hp)

Duration

16 Jan 2024
15 Mar 2024

Pace of study

100%

Form of study

Normal Daytime

Language of instruction

English

Course location

KTH Campus

Number of places

Places are not limited

Planned modular schedule

Application

For course offering

Spring 2024 Start 16 Jan 2024 programme students

Application code

60720

Contact

For course offering

Spring 2024 Start 16 Jan 2024 programme students

Contact

Markus Flierl

Examiner

No information inserted

Course coordinator

No information inserted

Teachers

No information inserted
Headings with content from the Course syllabus FEO3250 (Spring 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Information theory of discrete and continuous variables: Entropy, Kraft inequality, relative entropy, entropy rate, redundancy rate, mutual information, asymptotic equipartition.

Lossless coding: nonadaptive codes: Shannon, Huffmann, arithmetic codes. Universal and adaptive codes. Ziv-Lempel codes.

Rate-distortion theory: the rate-distortion function, Shannon lower bound, rate distribution over independent variables, reverse waterfilling, Blahut algorithm.

High-rate quantization: resolution-constrained and entropy-constrained quantization. Scalar and vector quantization.

Low-rate quantization: Lloyd training algorithm for resolution-constrained and entropy-constrained cases.

Transform coding: Orthonormal transforms, transform coding gain, Karhunen-Loeve transform, Energy concentration.

Predictive coding: MSE-optimal linear prediction, linear prediction gain, coding of prediction error, closed-loop prediction.

Intended learning outcomes

After the course, the student should be able to:

  • describe the general principles of rate distortion theory
  • assess given source coding schemes in the light of these principles
  • devise coding schemes for given sources
  • apply these principles to accomplish a project task
  • contribute to the research frontier in the area

Literature and preparations

Specific prerequisites

EQ1220 Signal Theory or equivalent

Recommended prerequisites

EQ1220 Signal Theory or equivalent

Equipment

No information inserted

Literature

No information inserted

Examination and completion

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

Grading scale

P, F

Examination

  • EXA1 - Examination, 12.0 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.

  • Homework problems: pass/fail
  • Written examination: pass/fail
  • Project: pass/fail

Other requirements for final grade

Homework, examination, and project

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

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

This course does not belong to any Main field of study.

Education cycle

Third cycle

Add-on studies

No information inserted

Contact

Markus Flierl

Postgraduate course

Postgraduate courses at EECS/Information Science and Engineering