Recursive Bayesian estimation: Difference between revisions

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*{{cite journal |first1=M. Sanjeev |last1=Arulampalam |first2=Simon |last2=Maskell |first3=Neil |last3=Gordon |title=A Tutorial on Particle Filters for On-line Non-linear/Non-Gaussian Bayesian Tracking |journal=IEEE Transactions on Signal Processing |volume=50 |issue= |pages=174–188 |year=2002 |doi= 10.1109/78.978374|url=http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.117.1144}}

*{{cite web |first1=Julien |last1=Diard |first2=Pierre |last2=Bessière |first3=Emmanuel |last3=Mazer |title=A survey of probabilistic models, using the Bayesian Programming methodology as a unifying framework |date=2003 |publisher=cogprints.org |url=http://cogprints.org/3755/1/Diard03a.pdf |format=PDF}}

*{{cite journal |first1=Alexander |last1=Volkov |title=Accuracy bounds of non-Gaussian Bayesian tracking in a NLOS environment |journal=Signal Processing |volume=108 | pages=498–508 |year=2015 |doi= 10.1016/j.sigpro.2014.10.025 |url=http://dx.doi.org/10.1016/j.sigpro.2014.10.025}}

* [http://www.math.u-bordeaux1.fr/~delmoral/simulinks.html Feynman-Kac models and interacting particle algorithms (a.k.a. Particle Filtering)] Theoretical aspects and a list of application domains of particle filters

*{{cite book |first1=Simo |last1=Särkkä |title=Bayesian Filtering and Smoothing |publisher=Cambridge University Press |year=2013 |url=http://becs.aalto.fi/~ssarkka/pub/cup_book_online_20131111.pdf |format=PDF}}