ADAPTIVE SUBSAMPLING OF MULTIDOMAIN SIGNALS WITH PRODUCT GRAPHS - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

ADAPTIVE SUBSAMPLING OF MULTIDOMAIN SIGNALS WITH PRODUCT GRAPHS

Pierre Humbert
Laurent Oudre

Résumé

In this paper, we propose an adaptive subsampling method for multidomain signals based on the constrained learning of a product graph. Given an input multidomain signal, we search for a product graph on which the signal is bandlimited, i.e. have limited spectral occupancy. The subsampling procedure described in this article is composed of two successive steps. First, we use the input data to learn a graph that will be optimized to favor efficient sampling. Then, we derive an algorithm for choosing the best nodes and provide a sampling strategy for multidomain signals. Experiments on synthetic data and two real datasets show the efficiency of the proposed method and its relevance for multidomain data compression and storing.
Fichier principal
Vignette du fichier
ICASSP2021 (1).pdf (466.63 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03671309 , version 1 (18-05-2022)

Identifiants

Citer

Théo Gnassounou, Pierre Humbert, Laurent Oudre. ADAPTIVE SUBSAMPLING OF MULTIDOMAIN SIGNALS WITH PRODUCT GRAPHS. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2021, Jun 2021, Toronto, France. pp.5295-5299, ⟨10.1109/ICASSP39728.2021.9413459⟩. ⟨hal-03671309⟩
19 Consultations
36 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More