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Neighborhood-Preserving Translations on Graphs

N. Grelier, B. Pasdeloup, J. Vialatte and V. Gripon, "Neighborhood-Preserving Translations on Graphs," in Proceedings of GlobalSIP, pp. 410--414, October 2016.

In many domains (e.g. Internet of Things, neuroimaging) signals are naturally supported on graphs. These graphs usually convey information on similarity between the values taken by the signal at the corresponding vertices. An interest of using graphs is that it allows to define ad hoc operators to perform signal processing. Among them, ones of paramount importance in many tasks are translations. In this paper we propose new definitions of translations on graphs using a few simple properties. Namely we propose to define translations as functions from vertices to adjacent ones, that preserve neighborhood properties of the graph. We show that our definitions, contrary to other works on the subject, match usual translations on grid graphs.


Bibtex
@inproceedings{GrePasViaGri201610,
  author = {Nicolas Grelier and Bastien Pasdeloup and
Jean-Charles Vialatte and Vincent Gripon},
  title = {Neighborhood-Preserving Translations on
Graphs},
  booktitle = {Proceedings of GlobalSIP},
  year = {2016},
  pages = {410--414},
  month = {October},
}




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