The problem of design and evaluation of binary hypothesis tests based on a set of available observations is considered. A so-called structured adaptive network (SAN) configuration for the modeling and implementation of a wide class of such tests is introduced. A general framework for the analysis and performance evaluation of a SAN is developed.
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