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dc.contributor.authorElliott, R.-
dc.contributor.authorHaykin, S.-
dc.identifier.citationAutomatica, 2010; 46(3):620-624-
dc.description.abstractA discrete time filter is considered where both the observation and signal process have non-linear dynamics with additive Gaussian noise. Using the reference probability framework a convolution type Zakai equation is obtained which updates the unnormalized conditional density. Using first order approximations this equation can be solved recursively and the extended Kalman filter can be derived.-
dc.description.statementofresponsibilityRobert J. Elliott, Simon Haykin-
dc.publisherPergamon-Elsevier Science Ltd-
dc.rightsCopyright © 2010 Elsevier Ltd All rights reserved.-
dc.subjectExtended Kalman filter-
dc.subjectBayes’ rule-
dc.subjectZakai equation-
dc.subjectDiscrete time-
dc.titleA Zakai equation derivation of the extended Kalman filter-
dc.typeJournal article-
Appears in Collections:Aurora harvest
Mathematical Sciences publications

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