Course detail

Data Coding and Compression

FIT-KKOAcad. year: 2022/2023

Introduction to data compression theory. Lossy and lossless data compression, adaptive methods, statistical - Huffman and arithmetic coding, dictionary methods LZ77, LZ78, transform coding, Burrows-Wheeler transform.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

doc. Ing. Zdeněk Vašíček, Ph.D.

Department

Department of Computer Systems (UPSY)

Learning outcomes of the course unit

Theoretical background of advanced data processing using compression. Importance of advanced data compression.

Prerequisites

Knowledge of functioning of basic computer units.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

An evaluated project for 30 points. A final examination for 70 points.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

To give the students the knowledge of basic compression techniques, the methods for lossy and lossless data compression, their efficiency and hardware support for data compression.

Specification of controlled education, way of implementation and compensation for absences

Not applicable.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Sayood, K.: Introduction to Data Compression, Fifth Edition, 2017, ISBN 978-0-12809-474-7

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MBS , 1 year of study, summer semester, compulsory
    branch MIN , 0 year of study, summer semester, elective
    branch MIS , 0 year of study, summer semester, elective
    branch MPV , 1 year of study, summer semester, compulsory

  • Programme MITAI Master's

    specialization NADE , 0 year of study, summer semester, elective
    specialization NBIO , 0 year of study, summer semester, elective
    specialization NCPS , 0 year of study, summer semester, elective
    specialization NEMB , 0 year of study, summer semester, compulsory
    specialization NGRI , 0 year of study, summer semester, elective
    specialization NHPC , 0 year of study, summer semester, elective
    specialization NIDE , 0 year of study, summer semester, elective
    specialization NISD , 0 year of study, summer semester, elective
    specialization NISY up to 2020/21 , 0 year of study, summer semester, elective
    specialization NMAL , 0 year of study, summer semester, elective
    specialization NMAT , 0 year of study, summer semester, elective
    specialization NNET , 0 year of study, summer semester, elective
    specialization NSEC , 0 year of study, summer semester, elective
    specialization NSEN , 0 year of study, summer semester, elective
    specialization NSPE , 0 year of study, summer semester, elective
    specialization NVER , 0 year of study, summer semester, elective
    specialization NVIZ , 0 year of study, summer semester, elective
    specialization NISY , 0 year of study, summer semester, elective

  • Programme IT-MSC-2 Master's

    branch MBI , 0 year of study, summer semester, compulsory-optional
    branch MGM , 0 year of study, summer semester, compulsory-optional
    branch MMM , 0 year of study, summer semester, compulsory-optional
    branch MSK , 1 year of study, summer semester, compulsory-optional

  • Programme MITAI Master's

    specialization NEMB up to 2021/22 , 0 year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Ing. Zdeněk Vašíček, Ph.D.

Syllabus

  • 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.
  • Dictionary methods, LZ77, LZ78.
  • Variants of LZW.
  • Transform coding, Burrows-Wheeler transform.
  • Advanced methods of data compression.

Project

26 hod., compulsory

Teacher / Lecturer

doc. Ing. Zdeněk Vašíček, Ph.D.

Syllabus

Individual project assignment.

Elearning

eLearning: currently opened course