Lectures

• January 6, Entropy, typical sequences Lecture 0, Lecture 1.
• January 13, Memoryless source coding Lecture 2.
• January 20, Memoryless source coding, Huffman code, Shannon-Fano-Elias code, Shannon code and arithmetic coding Lecture 3.
• January 27, adaptative Huffman coding, universal coding of a source Lecture 4.
• February 3, Stationnary source, typical sequences, AEP Lecture 5.
• February 10, Channel coding, capacity, Shannon's second theorem Lecture 6.
• February 17, Linear codes, Hamming and Reed-Solomon codes, decoding, concatenated codes Lecture 7.
• February 24, Polar codes Lecture 8.
• March 9, Other applications of information theory : distributed data storage. Lecture 9

TD

• TD1 Exercises on entropy.
  Solution : solutions
• TD2 Huffman coding.
• TD3 Arithmetic coding.
• TD4 Lempel-Ziv Coding.
• TD6 A first example of an error-correcting code : the Nordstrom-Robinson code
• TD7 A second example of an error-correcting code : a concatenated code.
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• TD8 Polar codes (html)
  TD8 Polar codes
  
• TD9 An introduction to LDPC codes.
  

Schedule of the oral examination INF 563

Bibliography

• T. Cover, J. Thomas, "Elements of Information Theory". Wiley Series in Telecommunications, 1991.
• S. Roman, "Coding and Information Theory",Graduate Texts in Mathematics. Springer Verlag, New York - Berlin, 1992.