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In this paper, we consider multi-channel sampling (MCS) for graph signals. Wegenerally encounter full-band graph signals beyond the bandlimited one in manyapplications, such as piecewise constant/smooth and union of bandlimited graphsignals. Full-band graph signals can be represented by a mixture of multiplesignals conforming to different generation models. This requires the analysisof graph signals via multiple sampling systems, i.e., MCS, while existingapproaches only consider single-channel sampling. We develop a MCS frameworkbased on generalized sampling. We also present a sampling set selection (SSS)method for the proposed MCS so that the graph signal is best recovered.Furthermore, we reveal that existing graph filter banks can be viewed as aspecial case of the proposed MCS. In signal recovery experiments, the proposedmethod exhibits the effectiveness of recovery for full-band graph signals.

Multi-channel Sampling on Graphs and Its Relationship to Graph Filter Banks