460-6011/04 – Data Compression (KOD)
| Gurantor department | Department of Computer Science | Credits | 10 |
| Subject guarantor | doc. Mgr. Jiří Dvorský, Ph.D. | Subject version guarantor | prof. Ing. Jan Platoš, Ph.D. |
| Study level | postgraduate | Requirement | Choice-compulsory type B |
| Year | | Semester | winter + summer |
| | Study language | English |
| Year of introduction | 2019/2020 | Year of cancellation | |
| Intended for the faculties | FEI | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
The aim is to deepen the knowledge gained in the Master's program. Students will study a selected area of data compression, implement the selected algorithms, they propose modifications, etc., carry out experiments and prepare a short, research (technical) report.
Teaching methods
Individual consultations
Summary
The course focuses on lossless and lossy compression methods, development of special methods of compression - the compression of large data sets and conversely short data, compression of semistructured data, compression of XML data. Fractal image compression, natural language compression will be discussed as well.
Compulsory literature:
K.Sayood. Introduction to Data Compression. Academic Press, 2006.
D.Salomon. Data Compression. Springer Verlag, 2004.
Recommended literature:
http://compression-links.info/
Vybrané články z konferencí a časopisů.
Way of continuous check of knowledge in the course of semester
Ongoing review of learning activities and assignments as part of regular
consultations. If the student's assignments also include publishing,
the relevant article will be presented in the course.
E-learning
Other requirements
Additional requirements for the student are not.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
The course focuses on lossless and lossy compression methods, development of special methods of compression - the compression of large data sets and conversely short data, compression of semistructured data, compression of XML data. Fractal image compression, natural language compression will be discussed as well.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction