Title:

Data Coding and Compression

Code:KKO
Ac.Year:2018/2019
Sem:Summer
Curriculums:
ProgrammeField/
Specialization
YearDuty
IT-MSC-2MBI-Compulsory-Elective - group S
IT-MSC-2MBS1stCompulsory
IT-MSC-2MGM-Compulsory-Elective - group G
IT-MSC-2MIN-Elective
IT-MSC-2MIS-Elective
IT-MSC-2MMI-Elective
IT-MSC-2MMM-Compulsory-Elective - group B
IT-MSC-2MPV1stCompulsory
IT-MSC-2MSK1stCompulsory-Elective - group C
Language of Instruction:Czech
Credits:5
Completion:credit+exam (written)
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:2600026
ExamsTestsExercisesLaboratoriesOther
Points:7000030
Guarantor:Vašíček Zdeněk, doc. Ing., Ph.D. (DCSY)
Deputy guarantor:Šimek Václav, Ing. (DCSY)
Lecturer:Drábek Vladimír, doc. Ing., CSc. (DCSY)
Vašíček Zdeněk, doc. Ing., Ph.D. (DCSY)
Instructor:Šimek Václav, Ing. (DCSY)
Faculty:Faculty of Information Technology BUT
Department:Department of Computer Systems FIT BUT
Schedule:
DayLessonWeekRoomStartEndLect.Gr.Groups
Monexam - 2. oprava2019-06-03E104 09:0010:501MIT 2MIT
Tueexam - 1. oprava2019-05-28E112 09:0010:501MIT 2MIT
Tueexam - řádná2019-05-21D105 12:0013:501MIT 2MIT

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, hardware support for data compression.
Description:
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. Hardware support for data compression.
Knowledge and skills required for the course:
Knowledge of functioning of basic computer units.
Subject specific learning outcomes and competencies:
Theoretical background of advanced data processing using compression.
Generic learning outcomes and competencies:
Syllabus of lectures:

• Introduction to compression theory.
• Basic compression methods.
• Statistical and dictionary methods.
• Huffman coding.
• Arithmetic coding. Text compression.
• Lossy and lossless data compression.
• Dictionary methods, LZ77, 78.
• Variants of LZW.
• Transform coding, Burrows-Wheeler transform.
• Other methods.
• Hardware support for data compression, MXT.
Syllabus - others, projects and individual work of students:
Individual project assignment.
Fundamental literature:

• Salomon, D.: Data Compression. The Complete Reference, Second Edition, Springer 2000, ISBN 0-387-95045-1
Study literature:

• Lecture notes and study supports in e-format.
Progress assessment:
Project designing and presentation.
Exam prerequisites:
Project designing and presentation. Min 10 points.