Introduction to statistical signal processing - 4AMAC469

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Number of hours
- Lectures : 9.0
- Tutorials : 9.0
- Laboratory works : 9.0
- Projects : -
- Internship : -
- Written tests : -
ECTS : 1.5
Officials : Romain SIRAGUSA

Goals

At the end of the class, the student will be able to solve simple problem on statistical signal processing like the quantification of a random signal, the filtering, the calculus of the signal to noise ratio of a transmission.
The student will also be able to evaluate and analyze the characteristics of a signal and a random variable like the DC component, the power, the energy, etc.

Content

1. Basics on probabilistic theory
2. Definition of a system, a signal and a random variable
3. Temporal characteristics of a continuous and a discrete random signals

DC component, power, autocorrelation
4. Statistical characteristique of a random variable
moment, variance, repartition function, density
5. Characteristics of a system
stationarity, ergodism
6. Noise : mathematical formalism
7. Random signal filtering

Prerequisites

basics on signal processing, electronics, mathematics : statistics, complex,

Tests

moyenne : mean of the course
Exam : examen
TP : lab

Calendar

The course exists in the following branches:

Curriculum - EIS (Apprenticeship) - App - Semester 7

see the course schedule for 2022-2023

Additional Information

Course ID : 4AMAC469
Course language(s):

The course is attached to the following structures:

Team Automatic and Signal processing

You can find this course among all other courses.

Bibliography

[1] Charbit, "Eléments de théorie du signal : les signaux aléatoires", Ellipses.
[2] Delmas, "Eléments de théorie du signal : les signaux déterministes", Ellipses
[3] Max, "Méthodes et techniques de traitement du signal", Masson.
[4] Bellanger, "Traitement numérique du signal", Masson.
[5] De Coulon, "Théorie et traitement des signaux", Dunod.
[6] Kunt, "Traitement numérique des signaux", Dunod.
[7] Mannevielle-Esqieu, "Théorie du signal et composants", Dunod.