TSBK08 · 6 credits · Advanced level (A1N) · Elektroteknik, Medieteknik
Data Compression
Discontinued
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Part of 6 programmes
- Master's Programme in Data Science and Information Engineering
- Master of Science in Computer Science and Engineering
- Master of Science in Information Technology
- Master of Science in Computer Science and Software Engineering
- Master of Science in Applied Physics and Electrical Engineering - International
- Master of Science in Applied Physics and Electrical Engineering
About the course
Aim
After having taken this course, the student is expected to be able to
- Obtain a random model for a source, given data from the source.
- Analyze random sources and calculate theoretical limits for coding performance.
- Understand and explain the concept of codes.
- Understand and explain how the following coding methods work Huffman coding Golomb coding Arithmetic coding Lempel-Ziv coding Burrows-Wheeler's block transform
- Understand and explain how adaptive Huffman coding and adaptiv arithmetic coding works.
- Design different types of coders and calculate their coding performance, given random source models.
- Know where the coding methods are used in different standards.
- Implement different coding methods, test these on real data and report the results in writing.
Content
The course deals with coding and data compression from an information theoretic perspective. Subjects:
- Random models for sources
- Source coding theory
- Entropy
- Huffman coding
- Arithmetic coding
- Lempel-Ziv coding
- Burrows-Wheeler's block transform
- Adaptive coding methods
- Coding standards
- Fax coding
- Lossless image coding
- Examiner
- Harald Nautsch
- Scheduled hours
- 48 h
- Main field of study
- Elektroteknik, Medieteknik