Estimation of General Nonlinear State-Space Systems
2011 (English)Report (Other academic)
This paper presents a novel approach to the estimation of a general class of dynamic nonlinear system models. The main contribution is the use of a tool from mathematical statistics, known as Fishers’ identity, to establish how so-called “particle smoothing” methods may be employed to compute gradients of maximum-likelihood and associated prediction error cost criteria.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2011. , 8 p.
LiTH-ISY-R, ISSN 1400-3902 ; 3001
Nonlinear Systems, Maximum likelihood, System Identication, Fishers' identity.
IdentifiersURN: urn:nbn:se:liu:diva-97946ISRN: LiTH-ISY-R-3001OAI: oai:DiVA.org:liu-97946DiVA: diva2:650749
FunderSwedish Research CouncilSwedish Foundation for Strategic Research