Description

Learning Outcomes

By the end of this course, the students will be able to:

• characterize the main elements of a digital signal processing scheme, including ADC, DAC, anti-aliasing filter and reconstruction filter,


• compute the discrete Fourier transform, the z-transform of discrete signal,


• implement digital filters of the FIR or IIR type, and study the stability and the phase behavior of digital filters,


• compute the auto-correlation, cross correlation and PSD of discrete random signals,


• understand the need for designing an adaptive digital filter with coefficients computed based on LMS or RLS algorithm.


• use Matlab for simulations of digital signal processing.

Items

• Introduction


• Sampling, ADC and DAC,


• Discrete Fourier transform, FFT and z-transform,


• FIR filtering


• Design of FIR filters and applications


• IIR filtering


• Design of IIR filters and applications


• Introduction to discrete random signal processing,


• Adaptive filters


• Project: students will be asked to put in practice assimilated notions to carry out a project describing a practical application. This project will be developed using MATLAB and dedicated digital signal processing platforms.

Finalité

In this course we address:

• Analog to digital signal conversion concept,


• Sampling and analog to digital conversion


• Discrete signal Fourier and FFT analysis,


• FIR and IIR filtering,


• Introduction to random signal processing,


• Adaptive filters.

Compétences visées

• Provide the basics of digital signal processing, making the connection between theoretical analysis and applications.


• Be able to design and implement a processing device or software.


• Design and build a digital signal processing device.

Description des modalités d'évaluation

• Project mark plus final exam.

Project (40%) and Exam (60%).

Public

• Have, at least, bac + 2 level in electronics (BTS, DUT, DPCT).