Distributed decision fusion under unknown distributions
The problem of distributed decision fusion is studied in the case when the probability distributions of the individual detectors are not available. The detector system is available so that a training ...
Adaptive fusion processor paradigms for fusion of information acquired at different levels of detail
Alternative paradigms for fusion of a mix of information at the data, feature, and decision levels, acquired from multiple sources (sensors as well as feature extractors and/or decision processors) ar...
Adecentralized detection system operating in asynchronous mode is presented. Thelocal sensors generate their decisions asynchronously and convey them toa global decision maker (GDM). A sequential decision fusion schemeis implemented at the GDM in order to reach aglobal decision. It is assumed that local decisions are generatedaccording to a Poisson process at each local sensor. Aperformance comparison with the equivalent fixed-sample size test is presented.Truncation of the sequential test is also addressed.
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