Proc. SPIE. 5813, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2005
KEYWORDS: Information fusion, Sensors, Sensor performance, Frequency modulation, Fermium, Sensor fusion, Probability theory, Evolutionary algorithms, Data fusion, Algorithms
In this paper it is illustrated how Bayes equations and frequency data may use as a measure of performance for belief fusion algorithms. A review of Bayes equations for single and multiple sources is provided. A simple performance measure is then calculated and applied to some belief fusion examples from the literature. Their performance measures are qualitatively similar, but the quantitative differences among these techniques appear to be arbitrary.
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