4.6k citations · 13.8k across the 80 of their papers we have counts for
7 papers · 1 filter
Distributed Signal Processing via Chebyshev Polynomial Approximation
David I Shuman, Pierre Vandergheynst, Daniel Kressner +1
Unions of graph multiplier operators are an important class of linear operators for processing signals defined on graphs. We present a novel method to efficiently distribute the ap…
Sampling theorems and compressive sensing on the sphere
J. D. McEwen, G. Puy, J. -Ph. Thiran +3
We discuss a novel sampling theorem on the sphere developed by McEwen & Wiaux recently through an association between the sphere and the torus. To represent a band-limited signal e…
Implications for compressed sensing of a new sampling theorem on the sphere
J. D. McEwen, G. Puy, J. -Ph. Thiran +3
A sampling theorem on the sphere has been developed recently, requiring half as many samples as alternative equiangular sampling theorems on the sphere. A reduction by a factor of…
Universal and efficient compressed sensing by spread spectrum and application to realistic Fourier imaging techniques
Gilles Puy, Pierre Vandergheynst, Rémi Gribonval +1
We advocate a compressed sensing strategy that consists of multiplying the signal of interest by a wide bandwidth modulation before projection onto randomly selected vectors of an…
On Variable Density Compressive Sampling
Gilles Puy, Pierre Vandergheynst, Yves Wiaux
We advocate an optimization procedure for variable density sampling in the context of compressed sensing. In this perspective, we introduce a minimization problem for the coherence…
Clustering with Multi-Layer Graphs: A Spectral Perspective
Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst +1
Observational data usually comes with a multimodal nature, which means that it can be naturally represented by a multi-layer graph whose layers share the same set of vertices (user…