2025
Data Compression and Coding
Name: Data Compression and Coding
Code: INF13263M
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Informatics
Teaching languages: Portuguese, English
Languages of tutoring support: Portuguese, English
Regime de Frequência: E-learning
Sustainable Development Goals
Learning Goals
To acquire a global view of the lossless data compression problems and coding in noisy channels.
To understand the foundations of the Shannon information theory and the theoretical limits to data compression and channel capacity.
To know several common lossless data compression algorithms and channel coding algorithms.
To understand how information theory can be applied in other scientific areas.
To understand the foundations of the Shannon information theory and the theoretical limits to data compression and channel capacity.
To know several common lossless data compression algorithms and channel coding algorithms.
To understand how information theory can be applied in other scientific areas.
Contents
Introduction to the Shannon information theory.
Source-channel-Receiver.
Models for an information source: discrete memoryless source and sources with memory.
Markov chains. Stationary distributions.
Definition of entropy, conditional entropy and mutual information. Properties.
Source coding theorem.
Entropy encoding algorithms:
Shannon, Shannon-Fano and Huffman codes.
Shannon-Fano-Elias code and arithmetic coding.
Universal encoding algorithms:
Adaptive Huffman coding.
Lempel-Ziv codes: LZ77, LZ78, LZW.
Definition of channel capacity for discrete memoryless channels. Blahut and Arimoto algorithm.
Channel coding theorem.
Channel coding algorithms. Error detection and correction.
Parity check.
Repetition and Hamming codes.
Turbo codes and low density parity check codes (LDPC).
Introduction to lossy compression and rate-distortion theory.
Source-channel-Receiver.
Models for an information source: discrete memoryless source and sources with memory.
Markov chains. Stationary distributions.
Definition of entropy, conditional entropy and mutual information. Properties.
Source coding theorem.
Entropy encoding algorithms:
Shannon, Shannon-Fano and Huffman codes.
Shannon-Fano-Elias code and arithmetic coding.
Universal encoding algorithms:
Adaptive Huffman coding.
Lempel-Ziv codes: LZ77, LZ78, LZW.
Definition of channel capacity for discrete memoryless channels. Blahut and Arimoto algorithm.
Channel coding theorem.
Channel coding algorithms. Error detection and correction.
Parity check.
Repetition and Hamming codes.
Turbo codes and low density parity check codes (LDPC).
Introduction to lossy compression and rate-distortion theory.
Teaching Methods
The classes are divided into theoretical classes, where the theory and algorithms are presented, and practical classes, where the students solve problems both at the theoretical level and at the application level. The problems are solved in paper or computer.
Besides the lectures, the course is organized and supported in an electronic learning platform so that it is compatible with learning in tutorial or e-Learning methods.
Besides the lectures, the course is organized and supported in an electronic learning platform so that it is compatible with learning in tutorial or e-Learning methods.
Assessment
Assessment may take place either through continuous assessment or final assessment.
The continuous assessment regime consists of three tests and a project, with the final grade (FG) calculated using the following formula:
FG = 20% Test1 + 20% Test2 + 30% Test3 + 30% Project.
The final assessment regime consists of a final exam and a project, with the final grade calculated using the following formula:
FG = 70% Exam + 30% Project.
The project is carried out throughout the semester and is subject to an oral presentation and defense.
If deemed necessary to verify the extent to which the student has developed the knowledge and skills intended for the course unit, the teaching team may summon the student for an oral exam, pursuant to paragraph 13 of Article 110 of the Academic Regulations of the University of Évora, subject to the conditions set out in paragraph 4 of Article 116 and paragraph 1 of Article 118 of the same Regulations. The oral exam will account for 100% of the final grade for the course unit, replacing all other assessment components.
The continuous assessment regime consists of three tests and a project, with the final grade (FG) calculated using the following formula:
FG = 20% Test1 + 20% Test2 + 30% Test3 + 30% Project.
The final assessment regime consists of a final exam and a project, with the final grade calculated using the following formula:
FG = 70% Exam + 30% Project.
The project is carried out throughout the semester and is subject to an oral presentation and defense.
If deemed necessary to verify the extent to which the student has developed the knowledge and skills intended for the course unit, the teaching team may summon the student for an oral exam, pursuant to paragraph 13 of Article 110 of the Academic Regulations of the University of Évora, subject to the conditions set out in paragraph 4 of Article 116 and paragraph 1 of Article 118 of the same Regulations. The oral exam will account for 100% of the final grade for the course unit, replacing all other assessment components.
Teaching Staff
- Miguel José Simões Barão [responsible]
Accreditations and Certifications
