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Logo Faculté des Sciences et Techniques Le MansLogo Faculté des Sciences et Techniques  Le Mans
MA SCOLARITÉMA SCOLARITÉMA SCOLARITÉ
ACTUALITÉSACTUALITÉSACTUALITÉS

Signal analysis II

Présentation

  • Linear signal modeling

 

–   Identification of measured FRF

–   Autoregressive, Moving Average, Autoregressive and Moving Average models

–   Linear prediction

–   Modern Power Spectrum Estimation

–   Pisarenko, Prony methods, decomposition in subspaces

 

  • AcousAcoustic imaging with holography and beamforming

 

–   Bartlett processing, Capon and Music

–   Deconvolution

–   Holography for non stationary sources

Objectifs

  • Be able to implement autoregressive models
  • Be able to use and implement parametric Power Spectrum Estimation of a signal
  •  Be able to use and implement array processing methods

 

Conditions d'admission

Signal Analysis Refresh 1.1.6, elements of filtering, Z-transform 2.6

Examens

Written exam + practical report - 2 hours - all documents allowed

 

Informations complémentaires

Literature References

 

  • Digital Signal Processing: Principles, Algorithms and Applications (J. G. Proakis and D. G. Manolakis), Upper Saddle River, NJ: Prentice Hall, 1996.

 

  • Discrete-Time Signal Processing (A. V. Oppenheim and R. W. Schafer), Englewood Cliffs, NJ: Prentice Hall, 1989.

 

  • Modern Spectral Estimation (S. M. Kay), Englewood Cliffs, NJ: Prentice Hall, 1988.

 

  • Fourier Acoustics: Sound Radiation and Nearfield Acoustic Holography (E. G. Williams), Academic Press, New-York, 1999.

En bref

Crédits ECTS 2.5

Nombre d'heures 20.0

Période de l'année
Automne

Contact(s)

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