EE-726 / 4 crédits

Enseignant: Unser Michaël

Langue: Anglais

Remark: Next time: Fall 2024


Every 2 years


We cover the theory and applications of sparse stochastic processes (SSP). SSP are solutions of differential equations driven by non-Gaussian innovations. They admit a parsimonious representation in a wavelet basis and are relevant to coding, compressed sensing, and biomedical imaging.



Signal and image processing, sparsity, stochastic modeling, wavelets, compressed sensing.

Learning Prerequisites

Recommended courses

Theory of linear systems, Fourier transform, Signal processing, statistics.

Assessment methods

Midterm and final oral examination.


Moodle Link

Dans les plans d'études

  • Nombre de places: 20
  • Forme de l'examen: Multiple (session libre)
  • Matière examinée: Sparse stochastic processes
  • Cours: 28 Heure(s)
  • Exercices: 28 Heure(s)

Semaine de référence

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