Title:

Data Coding and Compression

Code:KKO
Ac.Year:2009/2010
Term:Summer
Curriculums:
ProgrammeBranchYearDuty
IT-MSC-2MBI1stCompulsory-Elective - group S
IT-MSC-2MBS1stCompulsory
IT-MSC-2MGM-Compulsory-Elective - group G
IT-MSC-2MGM.1stElective
IT-MSC-2MIN-Elective
IT-MSC-2MIN.-Elective
IT-MSC-2MIS-Elective
IT-MSC-2MIS.-Elective
IT-MSC-2MMI-Elective
IT-MSC-2MMM2ndCompulsory-Elective - group B
IT-MSC-2MPS1stElective
IT-MSC-2MPV1stCompulsory
IT-MSC-2MSK1stCompulsory-Elective - group C
Language:Czech
Credits:5
Completion:accreditation+exam (written)
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:2600026
 ExaminationTestsExercisesLaboratoriesOther
Points:7000030
Guarantee:Drábek Vladimír, doc. Ing., CSc., DCSY
Lecturer:Drábek Vladimír, doc. Ing., CSc., DCSY
Instructor:Drábek Vladimír, doc. Ing., CSc., DCSY
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 competences:
  Theoretical background of advanced data processing using compression.
Generic learning outcomes and competences:
  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 with checked results.
Exam prerequisites:
  Project designing with checked results.