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Data Compression, 6 credits
Datakompression, 6 hp
TSBK08
Main field of study
Electrical Engineering Media Technology and EngineeringCourse level
Second cycleCourse type
Programme courseExaminer
Harald NautschDirector of studies or equivalent
Lasse AlfredssonEducation components
Preliminary scheduled hours: 48 hRecommended self-study hours: 112 h
Available for exchange students
YesECV = Elective / Compulsory / Voluntary
Main field of study
Electrical Engineering, Media Technology and EngineeringCourse level
Second cycleAdvancement level
A1XCourse offered for
- Master's Programme in Communication Systems
- Computer Science and Engineering, M Sc in Engineering
- Industrial Engineering and Management - International, M Sc in Engineering
- Industrial Engineering and Management, M Sc in Engineering
- Information Technology, M Sc in Engineering
- Computer Science and Software Engineering, M Sc in Engineering
- Applied Physics and Electrical Engineering - International, M Sc in Engineering
- Applied Physics and Electrical Engineering, M Sc in Engineering
Entry requirements
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.
Prerequisites
Probability theoryIntended learning outcomes
After having taken this course, the student is expected to be able to
- Obtain a random model for a source, given data from the source.
- Analyze random sources and calculate theoretical limits for coding performance.
- Understand and explain the concept of codes.
- Understand and explain how the following coding methods work
- Huffman coding
- Golomb coding
- Arithmetic coding
- Lempel-Ziv coding
- Burrows-Wheeler's block transform
- Understand and explain how adaptive Huffman coding and adaptiv arithmetic coding works.
- Design different types of coders and calculate their coding performance, given random source models.
- Know where the coding methods are used in different standards.
- Implement different coding methods, test these on real data and report the results in writing.
Course content
The course deals with coding and data compression from an information theoretic perspective. Subjects:
- Random models for sources
- Source coding theory
- Entropy
- Huffman coding
- Arithmetic coding
- Lempel-Ziv coding
- Burrows-Wheeler's block transform
- Adaptive coding methods
- Coding standards
- Fax coding
- Lossless image coding
Teaching and working methods
The course consists of lectures, lessons and laboratory work.
Examination
| LAB2 | Small computer project | 2 credits | U, G |
| TEN1 | A written exam | 4 credits | U, 3, 4, 5 |
During the project, the students implement a couple of the coding
methods that are taught in the course and test them on several kinds of real data. The students can choose to work alone or in groups of two.
Grades
Four-grade scale, LiU, U, 3, 4, 5Other information
Supplementary courses: Image and Audio Coding
Department
Institutionen för systemteknikDirector of Studies or equivalent
Lasse AlfredssonExaminer
Harald NautschCourse website and other links
Education components
Preliminary scheduled hours: 48 hRecommended self-study hours: 112 h
Course literature
Kursen har inte någon hårt specificerad kurslitteratur. För den som även tänker läsa TSBK02/06 Bild- och ljudkodning rekommenderas den kursens huvudlitteratur: Khalid Sayood, "Introduction to Data Compression", Morgan Kaufmann Publishers, ISBN 978-0-12-415796-5| Code | Name | Scope | Grading scale |
|---|---|---|---|
| LAB2 | Small computer project | 2 credits | U, G |
| TEN1 | A written exam | 4 credits | U, 3, 4, 5 |
During the project, the students implement a couple of the coding
methods that are taught in the course and test them on several kinds of real data. The students can choose to work alone or in groups of two.
Kursen har inte någon hårt specificerad kurslitteratur. För den som även tänker läsa TSBK02/06 Bild- och ljudkodning rekommenderas den kursens huvudlitteratur: Khalid Sayood, "Introduction to Data Compression", Morgan Kaufmann Publishers, ISBN 978-0-12-415796-5
Note: The course matrix might contain more information in Swedish.
I = Introduce, U = Teach, A = Utilize
| I | U | A | Modules | Comment | ||
|---|---|---|---|---|---|---|
| 1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
| 1.1 Knowledge of underlying mathematics and science (G1X level) |
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X
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| 1.2 Fundamental engineering knowledge (G1X level) |
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
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X
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TEN1
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
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X
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LAB2
TEN1
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| 2.2 Experimentation, investigation, and knowledge discovery |
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X
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LAB2
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| 2.3 System thinking |
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X
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LAB2
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| 2.4 Attitudes, thought, and learning |
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X
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LAB2
TEN1
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| 2.5 Ethics, equity, and other responsibilities |
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
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X
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LAB2
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| 3.2 Communications |
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X
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LAB2
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| 3.3 Communication in foreign languages |
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X
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
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| 4.2 Enterprise and business context |
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| 4.3 Conceiving, system engineering and management |
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| 4.4 Designing |
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X
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LAB2
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| 4.5 Implementing |
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X
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LAB2
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| 4.6 Operating |
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| 5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
| 5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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| 5.4 Execution of research or development projects |
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| 5.5 Presentation and evaluation of research or development projects |
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