Theoretical Bounds in Minimax Decentralized Hypothesis Testing

Gökhan Gül; Abdelhak M. Zoubir

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arXiv · 1306.3618

Theoretical Bounds in Minimax Decentralized Hypothesis Testing

Gökhan Gül·Abdelhak M. Zoubir

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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.

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Gökhan Gül, Abdelhak M. Zoubir. 2016-04-24. Theoretical Bounds in Minimax Decentralized Hypothesis Testing. https://arxiv.org/abs/1306.3618

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