Random sampling of bandlimited signals on graphs

Abstract : We study the problem of sampling k-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, i.e., independent of the graph structure, and its performance depends on a parameter called the graph coherence. On the contrary, the second strategy is adaptive but yields optimal results. Indeed, no more than O(k log(k)) measurements are sufficient to ensure an accurate and stable recovery of all k-bandlimited signals. This second strategy is based on a careful choice of the sampling distribution, which can be estimated quickly. Then, we propose a computationally efficient decoder to reconstruct k-bandlimited signals from their samples. We prove that it yields accurate reconstructions and that it is also stable to noise. Finally, we conduct several experiments to test these techniques.
Type de document :
Pré-publication, Document de travail
Liste complète des métadonnées

Contributeur : Gilles Puy <>
Soumis le : vendredi 20 mai 2016 - 14:46:39
Dernière modification le : jeudi 15 novembre 2018 - 11:58:46


Fichiers produits par l'(les) auteur(s)


  • HAL Id : hal-01229578, version 2


Gilles Puy, Nicolas Tremblay, Rémi Gribonval, Pierre Vandergheynst. Random sampling of bandlimited signals on graphs. 2015. 〈hal-01229578v2〉



Consultations de la notice


Téléchargements de fichiers