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Signal inpainting on graphs via total variation minimization
journal contribution
posted on 2014-05-01, 00:00 authored by Siheng Chen, Aliaksei Sandryhaila, George Lederman, Zihao Wang, José M. F. Moura, Piervincenzo Rizzo, Jacobo BielakJacobo Bielak, James GarrettJames Garrett, Jelena KovacevicJelena KovacevicWe propose a novel recovery algorithm for signals with complex, irregular structure that is commonly represented by graphs. Our approach is a generalization of the signal inpainting technique from classical signal processing. We formulate corresponding minimization problems and demonstrate that in many cases they have closed-form solutions. We discuss a relation of the proposed approach to regression, provide an upper bound on the error for our algorithm and compare the proposed technique with other existing algorithms on real-world datasets