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Syllabus for

Academic year
ESS155 - Data compression
 
Owner: EMAST
6,0 Credits (ECTS 9)
Grading: TH - Five, Four, Three, Not passed
Level: C
Department: 32 - ELECTRICAL ENGINEERING


Teaching language: English

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 No Sp
0101 Examination 6,0 c Grading: TH   3,0 c 3,0 c   30 May 2006 am V,  31 Aug 2006 pm V

In programs

TTFYA ENGINEERING PHYSICS, Year 4 (elective)
TITEA SOFTWARE ENGINEERING, Year 4 (elective)
TITEA SOFTWARE ENGINEERING, Year 3 (elective)
TDATA COMPUTER SCIENCE AND ENGINEERING, Year 3 (elective)
TDATA COMPUTER SCIENCE AND ENGINEERING - Communications System, Year 4 (elective)
EMAST MSc PROGR. IN DIGITAL COMMUNICATION SYSTEMS AND TECHNOLOGY, Year 1 (compulsory)
TELTA ELECTRICAL ENGINEERING, Year 4 (elective)

Examiner:

Professor  Thomas Eriksson



Eligibility:

For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.

Course specific prerequisites

Random Processes, Signals and Systems.

Aim

The goal is to give the students basic knowledge of the theory and practice of data compression, and experience with both theoretical and practical problem-solving.

Content

The course covers two main areas of data compression: lossless compression techniques and lossy compression techniques.
In lossless data compression, the goal is to represent a digital data source with as few bits as possible, while still maintaining the possibility to reconstruct the original data perfectly; the process is invertible. The theoretical basis is given by information-theoretic concepts such as entropy and mutual information. Well-known techniques, for example Huffman coding and Lempel-Ziv coding, will be studied, and applications of lossless compression, such as WinZip, the UNIX compress command, facsimile compression etc, will be covered.
Lossy compression deals mainly with analogue sources such as speech, audio, images and video signals. The goal is again to represent the source in digital form, using as few bits as possible. Here, some coding losses are inevitable, and the algorithms must partly rely on the imperfections of the human ear and eye. Important concepts that will be studied in lossy compression are various transforms (wavelets, DCT, etc), linear prediction, and scalar/vector quantization. The applications include speech and audio coding algorithms, such as CELP, MP3, and the GSM mobile telephony algorithms, and image/video coding algorithms, such as JPEG and various MPEG video coding standards.

Organisation

The course is based on five small design projects, which together with the lectures, one per week, define the course. Exercises are also given.

Literature

Some modern data compression book. The course literature may vary from one year to next.
Currently: "Introduction to Data Compression, 2nd ed." by Khalid Sayood, Morgan Kaufmann Publishers 2000, ISBN 1-55860-558-4

Examination

All five design projects must be passed. A written exam concludes the course.


Page manager Published: Mon 28 Nov 2016.