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
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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, inPress. ⟨hal-02367868⟩



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