- Information representation: decorrelation coding and entropic coding.
- Information security: cryptographic coding.
- Information correction: channel coding theory and error-correcting codes.
At the end of this learning unit, the student is able to :
Given the learning outcomes of the "Master in Computer Science and Engineering" program, this course contributes to the development, acquisition and evaluation of the following learning outcomes:
- Basic notions in information theory; mutual information and entropy.
- Discrete source coding by fixed length-codes and variable-length codes.
- Decorrelation coding and coding gain notions.
- Basic notions in cryptology; secret-key and public-key cryptographic coding systems.
- Discrete memoryless channel; capacity notion; noisy channel coding theorem.
- General block coding theory; role of the minimum distance.
- Linear codes: generator matrix and parity-check matrix; syndrome decoding.
- Study of certain classes of linear block codes: cyclic codes and Reed-Solomon codes.
- Introduction to convolution codes.
Due to the COVID-19 crisis, the information in this section is particularly likely to change.The course consists of magistral courses as well as exercice sessions to explore the different aspects of the theory.
Due to the COVID-19 crisis, the information in this section is particularly likely to change.Written examination covering both theory and exercises. The exam may be divided into a closed-book part and an open-book part.
- LFSAB1402 : solid basic knowledge in computer science
- LFSAB1103 : solid basic knowledge in mathematics
- R.G. Gallager, "Information Theory and Reliable Communication" , John Wiley, 1968.
- F.J. MacWilliams and N.J.A. Sloane, "The Theory of Error-Correcting Codes" , North-Holland, 1977.