- Title
- Estimation of general nonlinear state-space systems
- Creator
- Ninness, Brett; Wills, Adrian; Schön, Thomas B.
- Relation
- 49th IEEE Conference on Decision and Control (CDC 2010). Proceedings of the 49th IEEE Conference on Decision and Control (Atlanta, GA 15-17 December, 2010) p. 6371-6376
- Publisher Link
- http://dx.doi.org/10.1109/CDC.2010.5717378
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2010
- Description
- 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.
- Subject
- maximum likelihood estimation; error statistics; estimation; state-space methods
- Identifier
- http://hdl.handle.net/1959.13/933240
- Identifier
- uon:11580
- Identifier
- ISBN:9781424477463
- Identifier
- ISSN:0743-1546
- Rights
- Copyright © 2010 IEEE. Reprinted from Proceedings of the 49th IEEE Conference on Decision and Control p. 6371-6376. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
- Language
- eng
- Full Text
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