Title:

Data Coding and Compression

Code:KKO
Ac.Year:2019/2020
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
MITAINADE-Elective
MITAINBIO-Elective
MITAINCPS-Elective
MITAINEMB-Compulsory
MITAINGRI-Elective
MITAINHPC-Elective
MITAINIDE-Elective
MITAINISD-Elective
MITAINISY-Elective
MITAINMAL-Elective
MITAINMAT-Elective
MITAINNET-Elective
MITAINSEC-Elective
MITAINSEN-Elective
MITAINSPE-Elective
MITAINVER-Elective
MITAINVIZ-Elective
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:Mrázek Vojtěch, Ing., Ph.D. (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
TuelecturelecturesD0206 09:0010:501MIT MBS MPV
 
Learning objectives:
  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.
Description:
  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. 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:
  Importance of advanced data compression.
Why is the course taught:
  Compression represents one of the most fundamental operations which is applied not only to improve the storage capacity, but also to lower the communication latency or increase throughput of the transmission channels. The goal of this course is to provide knowledge of compression techniques as well as the mathematical foundations of data compression. The students should develop transferable skills such as problem analysis and problem solving.
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.
  • Dictionary methods, LZ77, LZ78.
  • 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:
 
  • Sayood, K.: Introduction to Data Compression, Fifth Edition, 2017, ISBN 978-0-12809-474-7
  • Salomon, D.: Data Compression. The Complete Reference, Fourth Edition, Springer 2007, ISBN 978-1-84628-605-5
  • Sayood, K.: Lossless Compression Handbook,  2003, ISBN 978-0-12620-861-0
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.
 

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