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# EQ2845 Information Theory and Source Coding 7.5 credits

The course treats the principles underlying the encoding of speech, audio, video, and images at low bit rates. Source coding techniques such as scalar and vector quantization, orthogonal transforms, and linear prediction are introduced and their performance is analyzed theoretically. The theoretical bounds on the performance of source coders are discussed.

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Choose semester and course offering to see information from the correct course syllabus and course offering.

Headings with content from the Course syllabus EQ2845 (Spring 2019–) are denoted with an asterisk ( )

## Content and learning outcomes

### Course contents

This course introduces the principles of information theory and source coding, discusses fundamental source coding concepts, and provides hands-on experience for selected popular source coding algorithms. The course includes topics on information and entropy, lossless coding, Shannon's noiseless source coding theorem, lossy coding, rate distortion, Shannon's noisy source coding theorem, scalar and vector quantization, transform and predictive coding.

### Intended learning outcomes

After passing this course, participants should be able to

- describe and use the principles of information theory, like entropy, mutual information, asymptotic equipartition, data processing, prefix codes, Kraft inequality, noiseless source coding, maximum entropy, rate distortion, noisy source coding, Shannon lower bound, backward channel, reverse waterfilling, energy concentration, etc. to develop source coding algorithms,

- develop source coding schemes for lossless coding, like Huffman coding, arithmetic coding, Lempel-Ziv coding, universal source coding,

- develop source coding schemes for lossy coding, like scalar and vector quantization, Lloyd-Max quantization, entropy-constrained quantization, high-rate quantization, transform coding, predictive coding,

- implement (for example with MatLab) and assess the developed source coding schemes / algorithms,

- explain coding design choices using the principles of information theory,

- develop source coding schemes for a given source coding problem,

- model and assess source coding schemes using the principles of information theory,

- analyze given source coding problems, identify and explain the challenges, propose possible solutions, and explain the chosen design.

To achive higher grades, participants should also be able to

- solve more advanced problems in all areas mentioned above.

### Course disposition

No information inserted

## Literature and preparations

### Specific prerequisites

For single course students: 120 credits and documented proficiency in English B or equivalent.

Recommended: EQ1220 Signal Theory or equivalent

### Recommended prerequisites

EQ1220 Signal Theory or equivalent.

### Equipment

No information inserted

### Literature

T.M. Cover and J.A. Thomas, “Elements of Information Theory,” John Wiley & Sons, Inc., New York.

## Examination and completion

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

### Grading scale

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

### Examination

• INL1 - Assignment, 1.5 credits, grading scale: P, F
• TEN1 - Exam, 6.0 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.

Homework assignments 1.5 ECTS (P/F). Written exam 6 ECTS (A-F).

### Opportunity to complete the requirements via supplementary examination

No information inserted

### Opportunity to raise an approved grade via renewed examination

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 web

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 EQ2845

### Main field of study

Electrical Engineering

Second cycle

### Add-on studies

No information inserted

### Contact

Markus Flierl (mflierl@kth.se)

### Supplementary information

In this course, the EECS code of honor applies, see: http://www.kth.se/en/eecs/utbildning/hederskodex.