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100   $a20201127d2017      uy         |
101 0 $aeng
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182   $cc$2rdamedia
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200 00$aBayesian Inference
210   $cIntechOpen
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330 8 $aThe range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been extensively applied to logistics, medical services, search and rescue operations, or automotive safety, among others. This book takes a look at both theoretical foundations of Bayesian inference and practical implementations in different fields. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics, as well as a source document of fundamentals for intermediate Bayesian readers. 
606   $aKalman filtering$7Generated by AI
606   $aAdaptive filters$7Generated by AI
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615  0$aAdaptive filters
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996   $aBayesian inference$9671625
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