Stochastic PDEs and Wavelet Approximation
John Paul Ward, EPFL STI LIB

Seminar • 29 July 2014 • BM 4.233

Abstract
Stochastic partial differential equations (PDEs) are commonly used to model data for a variety of image processing tasks. In this talk, we address approximation theoretic tools for representing and interpreting data coming from medical imaging devices. Convergence and stability estimates for wavelet bases will be presented.