Applied Coding and Information Theory

This course introduces the concepts of coding and information theory with a focus on applications.

Covered topics will be taken from the following list and depend on the interests of the students:

1. Introduction to entropy and information

2. Data compression

  • Shannon source coding theorem
  • Huffman coding
  • Dictionary techniques
  • Arithmetic coding
  • Asymmetric numerical systems and modern standards (e.g. Apple, Facebook and Google)

3. Information theory, gambling and portfolio theory

4. Communication over a noisy channel

  • Communication channel and capacity
  • Channel coding theorem
  • Error-correcting codes
  • Real channels

5. Modern error-correcting codes and applications

  • Message passing algorithms
  • Convolutional and turbo codes
  • Low-density parity-check codes
  • Rateless codes and streaming
  • Polar codes

6. Codes and information theory for distributed storage systems on the cloud
 

The organizer of this teaching unit and its evaluation is the Faculty of Science of the University of Neuchâtel. Note that the registration procedure and deadlines are different from the JMCS.
 

Learning Outcomes: 
  • Formulate and demonstrate the fundamental concepts of information theory
  • Establish the principles of data compression and error correction
  • Categorise and demonstrate the different tradeoffs and applications of data compression and error-correcting coding techniques
     
Type: 
Course
Semester: 
S2019
ECTS: 
5
Lecturer: 
Site: 
N
Code: 
32089
62089
Language: 
english
Period: 
weekly
Schedule: 
Friday: 8:15 - 12:00
Location: 
UniNE, Unimail
Room: 
B104
Evaluation type: 
oral exam
Comment: 

First Lecture
The first lecture will take place on Friday, 22.02.2019 at 08:15 in UniNE, Unimail, room B104.

Course page
The course page can be found at https://moodle.unine.ch/course/view.php?id=2759.