Course details
Data Coding and Compression
KKO Acad. year 2019/2020 Summer semester 5 credits
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.
Guarantor
Course coordinator
Language of instruction
Completion
Time span
- 26 hrs lectures
- 26 hrs projects
Assessment points
- 70 pts final exam (written part)
- 30 pts projects
Department
Lecturer
Instructor
Subject specific learning outcomes and competences
Theoretical background of advanced data processing using compression.
Importance of advanced data compression.
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.
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.
Prerequisite knowledge and skills
Knowledge of functioning of basic computer units.
Study literature
- Lecture notes and study supports in e-format.
- 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
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.
Progress assessment
Project designing and presentation.
Exam prerequisites:
Project designing and presentation. Min 10 points.
Exam prerequisites
Project designing and presentation. Min 10 points.
Course inclusion in study plans
- Programme IT-MGR-2, field MBI, MGM, MMM, any year of study, Compulsory-Elective
- Programme IT-MGR-2, field MBS, MPV, 1st year of study, Compulsory
- Programme IT-MGR-2, field MIN, MIS, MMI, any year of study, Elective
- Programme IT-MGR-2, field MSK, 1st year of study, Compulsory-Elective
- Programme MITAI, field NADE, NBIO, NCPS, NGRI, NHPC, NIDE, NISD, NISY, NMAL, NMAT, NNET, NSEC, NSEN, NSPE, NVER, NVIZ, any year of study, Elective
- Programme MITAI, field NEMB, any year of study, Compulsory