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Titlebook: Mathematics of Data Fusion; I. R. Goodman,Ronald P. S. Mahler,Hung T. Nguyen Book 1997 Springer Science+Business Media B.V. 1997 Algebra.c

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Introductionnformation. Typically, such evidence involves various types of uncertainty which must be utilized in order to make good decisions. Technically speaking, the methodologies involved in accomplishing the above goal has been given a variety of names including: “data fusion”, “information fusion”, “combi
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Finite Random Setss the stage by developing the mathematical cornerstone of this approach: the concept of a .. The necessary mathematical preliminaries—topological spaces of finite sets, hybrid discrete-continuous spaces and hybrid integrals, etc.—are set forth in Section 4.1. Section 4.2 introduces the . and the ..
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Finite-Set Statistics5.1 we show that the basic concepts of elementary statistics—expectations, covariances, prior and posterior densities, etc.—have direct analogs in the multisensor, multitarget realm. In section 5.2 we show how the basic elements of parametric estimation theory—maximum likelihood estimator (MLE), max
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Introduction to the Conditional and Relational Event Algebra Aspects of Data Fusionched to it. When the uncertainty corresponding to each source is provided via the probability of a single unconditional event, standard probability and statistics techniques are adequate for dealing with the problem. However, it often arises that uncertainty is not provided in such a format. This ca
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