DocumentCode
404389
Title
Robust noncausal filtering
Author
Einicke, Garry
Author_Institution
Exploration & Min., CSIRO, Kenmore, Qld., Australia
Volume
1
fYear
2003
fDate
9-12 Dec. 2003
Firstpage
386
Abstract
Filter asymptotes are developed for output estimation and input estimation problems which lead to bounds on the spectrum of the estimation error and a priori estimates for the scalar γ in the H∞ design. State-space formulations for the optimal minimum-mean-square-error and suboptimal noncausal filters are presented. It is demonstrated that an H∞ approach can improve on conventional maximum-likelihood and conditional-mean techniques in a speech filtering application.
Keywords
H∞ control; filtering theory; maximum likelihood estimation; mean square error methods; parameter estimation; state-space methods; H∞ design; conditional mean techniques; conventional maximum likelihood; estimation error; input estimation; optimal minimum mean square error; output estimation; parameter estimation; robust noncausal filtering; speech filtering; state-space formulations; suboptimal noncausal filters; Australia; Estimation error; Filtering; Maximum likelihood estimation; Nonlinear filters; Riccati equations; Robustness; Speech; State estimation; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
ISSN
0191-2216
Print_ISBN
0-7803-7924-1
Type
conf
DOI
10.1109/CDC.2003.1272592
Filename
1272592
Link To Document