Theoretical Bounds in Minimax Decentralized Hypothesis Testing
Information Theory
2016-04-26 v3 math.IT
Abstract
Minimax decentralized detection is studied under two scenarios: with and without a fusion center when the source of uncertainty is the Bayesian prior. When there is no fusion center, the constraints in the network design are determined. Both for a single decision maker and multiple decision makers, the maximum loss in detection performance due to minimax decision making is obtained. In the presence of a fusion center, the maximum loss of detection performance between with- and without fusion center networks is derived assuming that both networks are minimax robust. The results are finally generalized.
Cite
@article{arxiv.1306.3618,
title = {Theoretical Bounds in Minimax Decentralized Hypothesis Testing},
author = {Gökhan Gül and Abdelhak M. Zoubir},
journal= {arXiv preprint arXiv:1306.3618},
year = {2016}
}
Comments
Submitted to IEEE Trans. on Signal Processing