Subgraph detection using graph signals

Sundeep Prabhakar Chepuri, Geert Leus

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

In this paper we develop statistical detection theory for graph signals. In particular, given two graphs, namely, a background graph that represents an usual activity and an alternative graph that represents some unusual activity, we are interested in answering the following question: To which of the two graphs does the observed graph signal fit the best? To begin with, we assume both the graphs are known, and derive an optimal Neyman-Pearson detector. Next, we derive a suboptimal detector for the case when the alternative graph is not known. The developed theory is illustrated with numerical experiments.
Original languageEnglish (US)
Title of host publication2016 50th Asilomar Conference on Signals, Systems and Computers
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages532-535
Number of pages4
ISBN (Print)9781538639542
DOIs
StatePublished - Mar 6 2017
Externally publishedYes

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