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Graph signals classification using total variation and graph energy informations
2017
2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. This is an author-deposited version published in: https://sam.ensam.eu Handle ID Abstract-In this work, we consider the problem of graph signals classification. We investigate the relevance of two attributes, namely the total variation (TV) and the graph energy (GE) for graph signals classification. The TV is a compact and informative attribute
doi:10.1109/globalsip.2017.8309043
dblp:conf/globalsip/AhmedDB17
fatcat:nkdligmocrgozdzaangfc7aaiq