Using the Bayesian inference framework, this book enables the reader to design and develop mathematically sound algorithms for dealing with tracking problems involving multiple targets, multiple sensors, and multiple platforms. It shows how non-linear Multiple Hypothesis Tracking and the Theory of United Tracking are successful methods when multiple target tracking must be performed without contacts or association. With detailed examples illustrating the developed concepts, algorithms, and approaches, the book helps the reader track when observations are non-linear functions of target site, when the target state distributions or measurements error distributions are not Gaussian, when notions of contact and association are merged or unresolved among more than one target, and in low data rate and low signal to noise ratio situations.
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Lawrence D. Stone is Chief Operating Officer at Metron, Inc. He received his Ph.D. and MS in mathematics from Purdue University. Carl A. Barlow is an independent scientific consultant. He holds S.B. and S.M. degrees in theoretical physics from MIT. Thomas L. Corwin is Chief Executive Officer of Metron, Inc. He received his Ph.D and MS in statistics from Princeton University.
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Da: Greenworld Books, Arlington, TX, U.S.A.
Condizione: good. Fast Free Shipping â" Good condition book with a firm cover and clean, readable pages. Shows normal use, including some light wear or limited notes highlighting, yet remains a dependable copy overall. Supplemental items like CDs or access codes may not be included. Codice articolo GWV.1580530249.G
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Condizione: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. Codice articolo Z1-K-026-02511
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hardcover. Condizione: New. In shrink wrap. Looks like an interesting title! Codice articolo Q-1580530249
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Da: moluna, Greven, Germania
Condizione: New. Using the Bayesian inference framework, this book enables the reader to design and develop mathematically sound algorithms for dealing with tracking problems involving multiple targets, multiple sensors, and multiple platforms.Über den Autor. Codice articolo 596340250
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Da: AHA-BUCH GmbH, Einbeck, Germania
Buch. Condizione: Neu. Neuware - Get the solutions to your most challenging tracking problems with this up-to-date resource. Using the Bayesian inference framework, the book helps you design and develop mathematically sound algorithms for dealing with tracking problems involving multiple targets, multiple sensors, and multiple platforms. Codice articolo 9781580530248
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