IEEE Transactions on Aerospace and Electronic Systems · 1992 · 197 citations · 6 references
ComputingMathematicsInformation TheoryProbability TheorySensor FusionData AssociationDecision-level FusionSignal Detection TheoryBayesian FusionData FusionDetectorsInformation-theoretic FusionLocal Binary PatternsMulti-sensor Data FusionProbability Density FunctionsStatistical Data Fusion
Z. Chair and P.R. Varshney (1986) solved the data fusion problem for fixed binary local detectors with statistically independent decisions. Their solution is generalized by using the Bahadur-Lazarsfeld expansion of probability density functions. The optimal data fusion rule is developed for correlation local binary decisions, in terms of the conditional correlation coefficients of all orders. It is shown that when all these coefficients are zero, the rule coincides with the original Chair-Varshney design.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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Pattern Classification and Scene Analysis
Michael Thompson, Richard O. Duda, Peter E. Hart · Leonardo · 1974 · 4.5K citations
An Introduction to the Theory of Statistics