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Near-Optimal Graph Signal Sampling by Pareto Optimization
2021
Sensors
In this paper, we focus on the bandlimited graph signal sampling problem. To sample graph signals, we need to find small-sized subset of nodes with the minimal optimal reconstruction error. We formulate this problem as a subset selection problem, and propose an efficient Pareto Optimization for Graph Signal Sampling (POGSS) algorithm. Since the evaluation of the objective function is very time-consuming, a novel acceleration algorithm is proposed in this paper as well, which accelerates the
doi:10.3390/s21041415
pmid:33670548
fatcat:55yju544xrcm5j74aczrkekoma