Title:

Data Coding and Compression

Code:KKO
Ac.Year:2008/2009
Sem:Summer
Curriculums:
ProgrammeField/
Specialization
YearDuty
IT-MSC-2MGM.1stElective
IT-MSC-2MIN.-Elective
IT-MSC-2MIS.-Elective
IT-MSC-2MPS1stElective
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:Drábek Vladimír, doc. Ing., CSc. (DCSY)
Lecturer:Drábek Vladimír, doc. Ing., CSc. (DCSY)
Instructor:Šimek Václav, Ing. (DCSY)
Faculty:Faculty of Information Technology BUT
Department:Department of Computer Systems FIT BUT
 
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:
  Importance of advanced data compression.
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, 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.
 

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