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Adaptive Filtering

3EAH4 Adaptive Filtering Electronique et Physique appliquée S9
Cours : 15 h TD : 0 h TP : 18 h Projet : 0 h Total : 33 h
Responsable : Mathieu Pouliquen
Pré-requis
Courses of Mathematics of ENSICAEN, Signal Processing, Digital signal processing
Objectifs de l'enseignement
The course of adaptive filtering is intended acquisition by students of the basic tools for adaptive processing of signals. Several types of adaptive filtering methods are described: the sense of Wiener filtering, filtering in the sense of least squares and Kalman filtering. The implementation of either technique depends on the goal, the available information and how is implemented the filter. Consulting firms are available to enable students to acquire the first reflex. The course focuses particularly on a key application in telecommunications: the problem of equalization. This is analyzed in terms of signal processing and resolved through previous filtering techniques.
Programme détaillé
Introduction

Adaptive Filtering motivation:

in the sense of Wiener Filtering

Filtering in the sense of least squares

Application to Kalman Filtering problem

The problem of equalization

Equalization with learning

blind equalization

Conclusion
Applications (TD ou TP)
Adaptive filtering techniques taught in the course are used in some common applications such as echo cancellation, equalization and identification. The various labs are all oriented towards solving practical problems in real time or not. The implementation is done under Matlab / Simulink as well as DSP.
Compétences acquises
Techniques of adaptive filtering with a preferred application in the field of telecommunications.
Bibliographie
J. Proakis (2001). Digital Communications. McGraw Hill S. Haykin (2001). Communication Systems. Wiley. A. Glavieux et M. Joindot (1996). Communications Numériques. Masson. J. Proakis, M. Salehi and G. Bauch (2004). Contemporary Communication Systems using Matlab. Thomson Brooks.

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