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Publications associées (27)

Sound Field Reconstruction in a room through Sparse Recovery and its application in Room Modal Equalization

Vu Thach Pham

The acoustics of a room often refer to the quality of the room in terms of sound recording as well as sound reproduction. At low frequencies, where the wavelengths are of the same order of magnitude with the dimensions of the room, due to the standing wave ...

EPFL2021

Fourier Sampling in Signal Processing and Numerical Linear Algebra

Amir Zandieh

This thesis focuses on developing efficient algorithmic tools for processing large datasets. In many modern data analysis tasks, the sheer volume of available datasets far outstrips our abilities to process them. This scenario commonly arises in tasks incl ...

EPFL2020

Wavelet-Fourier CORSING techniques for multidimensional advection-diffusion-reaction equations

Fabio Nobile

We present and analyze a novel wavelet-Fourier technique for the numerical treatment of multidimensional advection–diffusion–reaction equations based on the COmpRessed SolvING (CORSING) paradigm. Combining the Petrov–Galerkin technique with the compressed ...

2021

Accelerated MP2RAGE imaging using Cartesian phyllotaxis readout and compressed sensing reconstruction

Jean-Philippe Thiran, Reto Meuli, Tobias Kober, Tom Hilbert, Émilie Priscille Claire Mussard

Purpose MP2RAGE T-1-weighted imaging has been shown to be beneficial for various applications, mainly because of its good grey-white matter contrast, its B-1-robustness and ability to derive T(1)maps. Even using parallel imaging, the method requires long a ...

WILEY2020

Sparse Polynomial Chaos expansions using variational relevance vector machines

Fabio Nobile, Panagiotis Tsilifis

The challenges for non-intrusive methods for Polynomial Chaos modeling lie in the computational efficiency and accuracy under a limited number of model simulations. These challenges can be addressed by enforcing sparsity in the series representation throug ...

2020

TV-based reconstruction of periodic functions

Julien René Fageot, Matthieu Martin Jean-André Simeoni

We introduce a general framework for the reconstruction of periodic multivariate functions from finitely many and possibly noisy linear measurements. The reconstruction task is formulated as a penalized convex optimization problem, taking the form of a sum ...

IOP PUBLISHING LTD2020

Sparse and Parametric Modeling with Applications to Acoustics and Audio

Helena Peic Tukuljac

Recent advances in signal processing, machine learning and deep learning with sparse intrinsic structure of data have paved the path for solving inverse problems in acoustics and audio. The main task of this thesis was to bridge the gap between the powerfu ...

EPFL2020