Publication

Distributed Compressed Sensing: Sparsity Models and Reconstruction Algorithms Using Annihilating Filter

Publications associées (28)

Learning of robust spectral graph dictionaries for distributed processing

We consider the problem of distributed representation of signals in sensor networks, where sensors exchange quantized information with their neighbors. The signals of interest are assumed to have a sparse representation with spectral graph dictionaries. We ...

SPRINGEROPEN2018

Looking beyond Pixels : Theory, Algorithms and Applications of Continuous Sparse Recovery

Hanjie Pan

Sparse recovery is a powerful tool that plays a central role in many applications, including source estimation in radio astronomy, direction of arrival estimation in acoustics or radar, super-resolution microscopy, and X-ray crystallography. Conventional a ...

EPFL2018

Sampling the Multiple Facets of Light

Gilles Baechler

The theme of this thesis revolves around three important manifestations of light, namely its corpuscular, wave and electromagnetic nature. Our goal is to exploit these principles to analyze, design and build imaging modalities by developing new signal proc ...

EPFL2018

Phonetic Subspace Features for Improved Query by Example Spoken Term Detection

Hervé Bourlard, Afsaneh Asaei, Dhananjay Ram

This paper addresses the problem of detecting speech utterances from a large audio archive using a simple spoken query, hence referring to this problem as "Query by Example Spoken Term Detection" (QbE-STD). This still open pattern matching problem has been ...

2018

Phaseless Diffraction Tomography With Regularized Beam Propagation

Michaël Unser, Alexandre Goy, Demetri Psaltis, Thanh-An Michel Pham, Ferréol Arnaud Marie Soulez, Joowon Lim, Emmanuel Emilien Louis Soubies

In recent years, researchers have obtained impressive reconstructions of the refractive index (RI) of biological objects through the combined use of advanced physics (nonlinear forward model) and regularization. Here, we propose an adaptation of these tech ...

IEEE2018

Adaptive Path Interpolation for Sparse Systems: Application to a Simple Censored Block Model

Nicolas Macris, Chun Lam Chan, Jean François Emmanuel Barbier

A new adaptive path interpolation method has been recently developed as a simple and versatile scheme to calculate exactly the asymptotic mutual information of Bayesian inference problems defined on dense factor graphs. These include random linear and gene ...

IEEE2018

Sampling Continuous-time Sparse Signals: A Frequency-domain Perspective

Martin Vetterli, Benjamin Bejar Haro

We address the problem of sampling and reconstruction of sparse signals with finite rate of innovation. We derive general conditions under which perfect reconstruction is possible for sampling kernels satisfying Strang-Fix conditions. Previous results on t ...

2018

Joint Estimation Of The Room Geometry And Modes With Compressed Sensing

Pierre Vandergheynst, Hervé Lissek, Vu Thach Pham, Helena Peic Tukuljac

Acoustical behavior of a room for a given position of microphone and sound source is usually described using the room impulse response. If we rely on the standard uniform sampling, the estimation of room impulse response for arbitrary positions in the room ...

IEEE2018