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• W4386602609 abstract "Due to the difficulty of decentralized inference with conditional dependent observations, and motivated by large-scale heterogeneous networks, we formulate a framework for decentralized detection with coupled observations. Each agent has a state, and the empirical distribution of all agents’ states or the type of network dictates the individual agents’ behavior. In particular, agents’ observations depend on both the underlying hypothesis as well as the empirical distribution of the agents’ states. Hence, our framework captures a high degree of coupling, in that an individual agent’s behavior depends on both the underlying hypothesis and the behavior of all other agents in the network. Considering this framework, the method of types, and a series of equicontinuity arguments, we derive the error exponent for the case in which all agents are identical and show that this error exponent depends on only a single empirical distribution. The analysis is extended to the multi-class case, and numerical results with state-dependent agent signaling and state-dependent channels highlight the utility of the proposed framework for analysis of highly coupled environments." @default.
• W4386602609 created "2023-09-12" @default.
• W4386602609 creator A5046918556 @default.
• W4386602609 creator A5072739163 @default.
• W4386602609 date "2023-09-08" @default.
• W4386602609 modified "2023-10-17" @default.
• W4386602609 title "Joint Detection and Communication over Type-Sensitive Networks" @default.
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• W4386602609 doi "https://doi.org/10.3390/e25091313" @default.
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• W4386602609 hasPublicationYear "2023" @default.
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