Course

EE-726: Sparse stochastic processes

Summary

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.

Lectures

Instructor

Michaël Unser

Expertise Image Processing, Medical Imaging, Biological Imaging, Wavelets, Splines, Multiresolution Michael Unser is Full Professor with EPFL’s school of Engineering and the academic director of EPFL's Center for Imaging, Lausanne, Switzerland. His primary areas of investigation are signal processing, biomedical imaging and applied functional analysis. He is internationally recognized for his research contributions to sampling theory, wavelets, the use of splines for image processing, stochastic processes,

Official source

https://edu.epfl.ch/coursebook/en/sparse-stochastic-processes-EE-726

Moodle Page

http://go.epfl.ch/EE-726

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Summary

Lectures

Instructor

Michaël Unser

Official source

https://edu.epfl.ch/coursebook/en/sparse-stochastic-processes-EE-726

Moodle Page

http://go.epfl.ch/EE-726

About this result

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