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https://hdl.handle.net/2440/63763
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DC Field | Value | Language |
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dc.contributor.author | Elliott, R. | - |
dc.contributor.author | Haykin, S. | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | Automatica, 2010; 46(3):620-624 | - |
dc.identifier.issn | 0005-1098 | - |
dc.identifier.uri | http://hdl.handle.net/2440/63763 | - |
dc.description.abstract | A 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.statementofresponsibility | Robert J. Elliott, Simon Haykin | - |
dc.language.iso | en | - |
dc.publisher | Pergamon-Elsevier Science Ltd | - |
dc.rights | Copyright © 2010 Elsevier Ltd All rights reserved. | - |
dc.subject | Extended Kalman filter | - |
dc.subject | Bayes’ rule | - |
dc.subject | Zakai equation | - |
dc.subject | Discrete time | - |
dc.title | A Zakai equation derivation of the extended Kalman filter | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.1016/j.automatica.2010.01.006 | - |
pubs.publication-status | Published | - |
Appears in Collections: | Aurora harvest Mathematical Sciences publications |
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