TY - GEN

T1 - Subgraph detection using graph signals

AU - Chepuri, Sundeep Prabhakar

AU - Leus, Geert

N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OSR-2015-Sensors-2700
Acknowledgements: This work was supported by the KAUST-MIT-TUD consortium grant OSR-2015-Sensors-2700.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

PY - 2017/3/6

Y1 - 2017/3/6

N2 - 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.

AB - 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.

UR - http://hdl.handle.net/10754/623599

UR - http://ieeexplore.ieee.org/document/7869097/

UR - http://www.scopus.com/inward/record.url?scp=85016304870&partnerID=8YFLogxK

U2 - 10.1109/acssc.2016.7869097

DO - 10.1109/acssc.2016.7869097

M3 - Conference contribution

SN - 9781538639542

SP - 532

EP - 535

BT - 2016 50th Asilomar Conference on Signals, Systems and Computers

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -