2016
DOI: 10.1186/s13634-016-0421-4
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Bandlimited graph signal reconstruction by diffusion operator

Abstract: Signal processing on graphs extends signal processing concepts and methodologies from the classical signal processing theory to data indexed by general graphs. For a bandlimited graph signal, the unknown data associated with unsampled vertices can be reconstructed from the sampled data by exploiting the spatial relationship of graph signal. In this paper, we propose a generalized analytical framework of unsampled graph signal and introduce a concept of diffusion operator which consists of local-mean and global… Show more

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Cited by 6 publications
(2 citation statements)
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Following publication of this article [1], it has come to our attention that the acknowledgements were captured incorrectly and the correct acknowledgements should include the following:
…”
mentioning
confidence: 99%
“…
Following publication of this article [1], it has come to our attention that the acknowledgements were captured incorrectly and the correct acknowledgements should include the following:
…”
mentioning
confidence: 99%
“…Note that the unsampled vertices of a graph signal are influenced by all the sampled vertices, which should not be limited in the local sets. Based on a local-mean diffusion operator and a global-bias diffusion operator, Yang et al [10] proposed the iterative global diffusion reconstruction (IGDR), which improved the IPR. In some potential applications, the obtained data may be a combination of signals associated with several vertices, Wang proposed the iterative local measurement reconstruction (ILMR) to reconstruct the bandlimited graph signals [11].…”
Section: Introductionmentioning
confidence: 99%