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In this paper, we present a unifying framework for distributed detection with dependent or independent observations. This novel framework utilizes an expanded hierarchical model by introducing a hidden variable. Facilitated by this new framework, we identify several classes of distributed detection problems with conditionally dependent observations whose optimal sensor signaling structure resembles...
Distributed detection with conditionally dependent observations is known to be a challenging problem in decentralized inference. This paper attempts to make progress on this problem by proposing a new framework for distributed detection that builds on a hierarchical conditional independence model. Through the introduction of a hidden variable that induces conditional independence among the sensor...
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