Autoregressive Moving Average Graph Filtering

@article{Isufi2017AutoregressiveMA,
  title={Autoregressive Moving Average Graph Filtering},
  author={Elvin Isufi and Andreas Loukas and Andrea Simonetto and Geert Leus},
  journal={IEEE Transactions on Signal Processing},
  year={2017},
  volume={65},
  pages={274-288}
}
One of the cornerstones of the field of signal processing on graphs are graph filters, direct analogs of classical filters, but intended for signals defined on graphs. This paper brings forth new insights on the distributed graph filtering problem. We design a family of autoregressive moving average (ARMA) recursions, which are able to approximate any desired graph frequency response, and give exact solutions for specific graph signal denoising and interpolation problems. The philosophy to… CONTINUE READING
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