Faculty of Information Technology, BUT

Course details

Data Coding and Compression

KKO Acad. year 2017/2018 Summer semester 5 credits

Introduction to data compression theory. Lossy and lossless data compression, adaptive methods, statistical - Huffman and arithmetic coding, dictionary methods LZ77, 78, transform coding, Burrows-Wheeler transform. Context methods. Hardware support for data compression, data compression in the memory hierarchy.

Guarantor

Language of instruction

Czech

Completion

Credit+Examination (written)

Time span

26 hrs lectures, 26 hrs projects

Assessment points

70 exam, 30 projects

Department

Lecturer

Instructor

Subject specific learning outcomes and competences

Theoretical background of advanced data processing using compression.

Generic learning outcomes and competences

Importance of advanced data compression.

Learning objectives

To give the students the knowledge of basic compression techniques, the methods for lossy and lossless data compression their efficiency, statistical and dictionary methods, transform and context  methods, and hardware support for data compression. Data compression in the memory hierarchy.

Prerequisite kwnowledge and skills

Knowledge of functioning of basic computer units.

Study literature

  • Lecture notes and study supports in e-format.

Fundamental literature

  • Salomon, D.: Data Compression. The Complete Reference, Second, Third and Fourth Edition, Springer 2000 etc., ISBN 0-387-95045-1
  • Sardashti, S., Arelakis, A., Stenstroem, P., Wood, D. A.: A Primer on Compression in the Memory Hierarchy, Morgan&Claypool 2016

Syllabus of lectures

  • Introduction to compression theory.
  • Basic compression methods.
  • Statistical and dictionary methods.
  • Huffman coding.
  • Adaptive Huffman coding.
  • Arithmetic coding. Text compression.
  • Lossy and lossless data compression. PPM.
  • Dictionary methods, LZ77, 78.
  • Variants of LZW.
  • Transform coding, Burrows-Wheeler transform.
  • Models of the context, context compression..
  • Hardware support for data compression, MXT. Data compression in the memory hierarchy. Zipp on HD.

Syllabus - others, projects and individual work of students

Individual project assignment.

Progress assessment

Project designing and presentation.

Exam prerequisites

Project designing and presentation. Min 10 p.

Course inclusion in study plans

  • Programme IT-MSC-2, field MBI, any year of study, Compulsory-Elective group S
  • Programme IT-MSC-2, field MBS, MPV, 1st year of study, Compulsory
  • Programme IT-MSC-2, field MGM, any year of study, Compulsory-Elective group G
  • Programme IT-MSC-2, field MIN, MIS, MMI, any year of study, Elective
  • Programme IT-MSC-2, field MMM, any year of study, Compulsory-Elective group B
  • Programme IT-MSC-2, field MSK, 1st year of study, Compulsory-Elective group C
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