Hardware complexity of binary distributed detection systems with isolated local Bayesian detectors

The authors have devised a simple suboptimal decentralized binary detection system where each local detector independently, and the data function center, are minimizing Bayesian risks (not necessarily identical). They compare the hardware volume of a system with identical local risks to that of an optimal centralized system which minimizes the same global risk for several mathematically tractable cases. The results can be used by designers of distributed detection systems (even less restricted than the ones that the authors consider in this work) to obtain upper bounds on the number of (decentralized) detectors which are required in order to guarantee prespecified performance