SAMPLING AND RECONSTRUCTION OF SIGNALS ON PRODUCT GRAPHS

Guillermo Ortiz-Jimenez, Mario Coutino, Sundeep Prabhakar Chepuri, Geert Leus
2018 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)  
In this paper, we consider the problem of subsampling and reconstruction of signals that reside on the vertices of a product graph, such as sensor network time series, genomic signals, or product ratings in a social network. Specifically, we leverage the product structure of the underlying domain and sample nodes from the graph factors. The proposed scheme is particularly useful for processing signals on large-scale product graphs. The sampling sets are designed using a low-complexity greedy
more » ... orithm and can be proven to be near-optimal. To illustrate the developed theory, numerical experiments based on real datasets are provided for sampling 3D dynamic point clouds and for active learning in recommender systems.
doi:10.1109/globalsip.2018.8646609 dblp:conf/globalsip/Ortiz-JimenezCC18 fatcat:fxeklgiey5fgfhp75wdj4dlini