Optimal filtering and Information transmission

Lecturer(s): Eric BLANCO, Julien HUILLERY, Laurent BAKO
Course ⋅ 12 hTC ⋅ 18 hPW ⋅ 4 hAutonomy ⋅ 14 h


The growth of communication and information processing systems has led to the emergence of new services. This development is based on an ever greater appropriation by the industrial world of information theory and signal processing methods whose theoretical bases have been presented in the first year course STI tc2. The objective of the course is to complete the presentation of the basics and methods of signal processing in order to acquire a complete set of tools to address the modeling, analysis and filtering of signals, as well as the operation of communication channels. These principles are found in applications such as telecommunications, software sensors or GPS positioning.


Stochastic signals, Generator system, Wiener filter, Kalman filter, Information theory, Source entropy, Channel capacity, Coding theorems


Part I: Optimal filtering 1- Stochastic signal 2- Wiener filtering 3- Kalman filtering Part II: Information Transmission 1- Elements of information theory 2- Entropy and source coding 3- Capacity and channel coding

Learning Outcomes

  • Modelling a signal and build a generator process.
  • Design an optimal filter in the time or frequency domains.
  • Implementing an entropic source coding scheme.
  • Calculate the limits of performance of a communication system.


Final mark = 70% knowledge + 30% know-how Knowledge = 80% final exam + 20% continuous assessment Know-how = 100% final exam (oral)