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Designing Convex Combination of Graph Filters

Abstract : In this letter, we study the problem of parametric modeling of network-structured signals with graph filters. Unlike the popular polynomial graph filters, which are based on a single graph shift operator, we consider convex combinations of graph shift operators particularly adapted to directed graphs. As the resulting modeling problem is not convex, we reformulate it as a convex optimization problem which can be solved efficiently. Experiments on real-world data structured by undirected and directed graphs are conducted. The results show the effectiveness of this method compared to other methods reported in the literature.
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Submitted on : Tuesday, January 14, 2020 - 5:49:12 PM
Last modification on : Wednesday, July 8, 2020 - 12:43:31 PM
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Fei Hua, Cédric Richard, Chen Jie, Haiyan Wang, Pierre Borgnat, et al.. Designing Convex Combination of Graph Filters. IEEE Signal Processing Letters, Institute of Electrical and Electronics Engineers, In press. ⟨hal-02367868⟩



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