Phelma Formation 2022

Spectral analysis - 4PMSASP9

  • Number of hours

    • Lectures 14.0
    • Projects 0
    • Tutorials 4.0
    • Internship 0
    • Laboratory works 4.0

    ECTS

    ECTS 1.5

Goal(s)

This course is intended for engineering students in order to offer both a theoretical basis and technical tools of spectral analysis for random signals. This course constitutes a basis for many applications in communications and digital signal processing.

Contact Bertrand RIVET, Laurent GIRIN, Pierre GRANJON

Content(s)

This course is intended for engineering students in order to offer both a theoretical basis and technical tools of spectral analysis for random signals. This course constitutes a basis for many applications in communications and digital signal processing.

  • Basic notion of the estimation theory
  • Maximum likelihood estimation
  • Spectral properties of random signals
  • Mean value estimation and correlation estimation
  • Power spectral density estimation
  • Non-parametric methods (correlogram and periodogram)
  • Parametric methods for spectral estimation (AR model)


Prerequisites

Basis of signal Processing (First year)
Random signal processing

Test

session 1 Written exam (2 hours) + continuous assessment (lab sessions attendance)
session 2 Written exam (2 hours)



session 1 N1 = 90% examen1 + 10% CC1
session 2 N2 = 90% examen2 + 10% CC1

Additional Information

Course list
Curriculum->SICOM->Semester 8

Bibliography

P. Stoica and R. Moses, “Spectral Analysis of Signals,” Prentice Hall, Upper Saddle River, 2005.
F. Castanié, "Analyse spectrale", Hermes, Paris, 2003.