Generalized Sampling on Graphs With Subspace and Smoothness Priors

@article{Tanaka2020GeneralizedSO,
  title={Generalized Sampling on Graphs With Subspace and Smoothness Priors},
  author={Yuichi Tanaka and Yonina C. Eldar},
  journal={IEEE Transactions on Signal Processing},
  year={2020},
  volume={68},
  pages={2272-2286}
}
We propose a framework for generalized sampling of graph signals that parallels sampling in shift invariant (SI) subspaces. This framework allows for arbitrary input signals which are not constrained to be bandlimited. Furthermore, the sampling and reconstruction filters may be different. We present design methods of the correction filter that compensate for these differences and lead to closed form expressions in the graph frequency domain. In this study, we consider two priors on graph… Expand
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