Signal and Image Processing - 4EUS4TSI

Statistical signal processing:

• spectral analysis (non-parametric methods, basic parametric methods)
  application ? vibroacoustic emissions of an industrial system
• optimal filtering (Wiener filtering, adaptive filtering),
  application ? filtering of biophysical signals

Image processing:

• digital image processing
• basics of morphological image processing
• Fourier transform and correlation
• inverse filtering

Mathematics for engineers: complex variable functions, Fourier transform, Laplace transform, Z transform.
Basics in continuous-time signal processing: deterministic and random signals, time domain and frequency domain representations, linear and time-invariant filters, modulation, sampling.
Basics in discrete-time signal processing: discrete Fourier transform, analysis and design of digital filters.

First session

• ER assessment : 3 hours supervised written
• EN assessment : work assignments + Lab reports

If distant learning mandatory:

• ER assessment : 3 hours homework
• EN assessment : work assignments + Lab reports

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Second session

• EN assessment: Retaking this assessment is not possible

ER 33% + EN 67%

The course exists in the following branches:

• Curriculum - Master's Degree in Engineering ASI - Semester 8

Course ID : 4EUS4TSI
Course language(s):

You can find this course among all other courses.

• Modern spectral estimation - theory and application, S.M. KAY, Prentice Hall, 1988

• Optimal Filtering, Brian D. O. Anderson and John B. Moore. Dover Publications, 2005

• Introduction au traitement d'images, D. Lingrand, Vuibert, 2d ed., 2008
• Digital Image Processing, W. K. Pratt, Wiley, 4th ed., 2007.