Estimation of General Nonlinear State-Space Systems
2010 (English)In: Proceedings of the 49th IEEE Conference on Decision and Control, 2010, 6371-6376 p.Conference paper (Refereed)
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
2010. 6371-6376 p.
Maximum likelihood estimation, State-space methods, Statistics
IdentifiersURN: urn:nbn:se:liu:diva-63594DOI: 10.1109/CDC.2010.5717378ISBN: 978-1-4244-7745-6OAI: oai:DiVA.org:liu-63594DiVA: diva2:380819
The 49th IEEE Conference on Decision and Control, Atlanta, GA, USA, 15-17 December, 2010
FunderSwedish Research CouncilSwedish Foundation for Strategic Research