460-6011/03 – Data Compression (KOD)

Gurantor departmentDepartment of Computer ScienceCredits10
Subject guarantordoc. Mgr. Jiří Dvorský, Ph.D.Subject version guarantordoc. Ing. Jan Platoš, Ph.D.
Study levelpostgraduateRequirementChoice-compulsory type B
YearSemesterwinter + summer
Study languageCzech
Year of introduction2019/2020Year of cancellation
Intended for the facultiesFEIIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
PLA06 doc. Ing. Jan Platoš, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Examination 28+0
Combined Examination 28+0

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

E-learning

Další požadavky na studenta

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

Combined form (validity from: 2019/2020 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Examination Examination  
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2019/2020 (P0613D140005) Computer Science P Czech Ostrava Choice-compulsory type B study plan
2019/2020 (P0613D140005) Computer Science K Czech Ostrava Choice-compulsory type B study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner