Blar i NTNU Open på forfatter "Elias, Vitor"

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    • Adaptive Graph Filters in Reproducing Kernel Hilbert Spaces: Design and Performance Analysis 

      Elias, Vitor; Gogineni, Vinay Chakravarthi; Martins, Wallace; Werner, Stefan (Peer reviewed; Journal article, 2021)
      This paper develops adaptive graph filters that operate in reproducing kernel Hilbert spaces. We consider both centralized and fully distributed implementations. We first define nonlinear graph filters that operate on ...

    • Extended Adjacency and Scale-Dependent Graph Fourier Transform via Diffusion Distances 

      Elias, Vitor; Martin, Wallace; Werner, Stefan (Peer reviewed; Journal article, 2020)
      This article proposes the augmentation of the adjacency model of networks for graph signal processing. It is assumed that no information about the network is available, apart from the initial adjacency matrix. In the ...

    • Graph diffusion kernel LMS using random Fourier features 

      Gogineni, Vinay Chakravarthi; Elias, Vitor; Martins, Wallace; Werner, Stefan (Chapter, 2021)
      This work introduces kernel adaptive graph filters that operate in the reproducing kernel Hilbert space. We propose a centralized graph kernel least mean squares (GKLMS) approach for identifying the nonlinear graph filters. ...

    • Kernel regression on graphs in random Fourier features space 

      Elias, Vitor; Gogineni, Vinay Chakravarthi; Martins, Wallace; Werner, Stefan (Chapter, 2021)
      This work proposes an efficient batch-based implementation for kernel regression on graphs (KRG) using random Fourier features (RFF) and a low-complexity online implementation. Kernel regression has proven to be an efficient ...