2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDSPTM-12.5
Paper Title ADAPTIVE SUBSAMPLING OF MULTIDOMAIN SIGNALS WITH PRODUCT GRAPHS
Authors Théo Gnassounou, Pierre Humbert, Laurent Oudre, Ecole Normale Superieure Paris Saclay, France
SessionSPTM-12: Sampling, Filtering and Denoising over Graphs
LocationGather.Town
Session Time:Wednesday, 09 June, 16:30 - 17:15
Presentation Time:Wednesday, 09 June, 16:30 - 17:15
Presentation Poster
Topic Signal Processing Theory and Methods: [SIPG] Signal and Information Processing over Graphs
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract 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.