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Accueil > Formations > Master MVA > Présentation des cours
Sparse wavelet representations and classification
Lecturer : Stéphane MALLAT, (ENS Ulm)
Objective of the course :
The course introduces sparse wavelet representation techniques, for compression, noise removal and for audio and image classification.
Topics :
- Fourier transform, linear approximations and sampling theorems
- Time-frequency representations
- Wavelet orthogonal bases
- Adaptive and non-linear wavelet approximations
- Information theory for image and audio compression.
- Linear and non-linear noise removal
- Linear classifiers and curse of dimensionality
- Invariants for classification
- Deep Neural Networks
- Image and audio signal recognition
References :
Une explorations des signaux en ondelettes", S. Mallat, Éditions de l'Ecole Polytechnique.