Abstract

Summary form only given. The authors provide a unified representation for different decentralized detection network topologies. They first present the definition of the communication structure of organizations for team decision making. A decentralized detection system is assumed to consist of a number of local decision makers and a global decision maker. All decision makers are connected to each other in some fashion. For all interconnection structures, the global decision maker is responsible for making the final decision. The communication structure is specified in terms of a n*n matrix where n is the total number of detectors in a given system. By properly labeling the matrix with time indices, the generalized communication structure can represent a more general class of decentralized detection structures including the ones with feedback. The optimum design of any decentralized detection structure represented by its communication matrix under the Bayesian framework is considered. The person-by-person optimization methodology was employed to obtain the decision rules at all the detectors. A distributed detection system with peer communication is considered to demonstrate the versatility of the unified representation and design methodology. >

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