Sufficiently informative measurements for stability of approximate conditional mean estimates
Data(s) |
15/11/2012
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Resumo |
This paper establishes sufficient conditions to bound the error in perturbed conditional mean estimates derived from a perturbed model (only the scalar case is shown in this paper but a similar result is expected to hold for the vector case). The results established here extend recent stability results on approximating information state filter recursions to stability results on the approximate conditional mean estimates. The presented filter stability results provide bounds for a wide variety of model error situations. |
Formato |
application/pdf |
Identificador | |
Publicador |
Engineers Australia |
Relação |
http://eprints.qut.edu.au/53898/6/53898.pdf Techakesari, Onvaree & Ford, Jason J. (2012) Sufficiently informative measurements for stability of approximate conditional mean estimates. In Proceedings of the 2nd Australian Control Conference, Engineers Australia, Sydney, N.S.W. http://purl.org/au-research/grants/ARC/LP100100302 |
Direitos |
Copyright 2012 Engineers Australia |
Fonte |
Australian Research Centre for Aerospace Automation; School of Electrical Engineering & Computer Science; Science & Engineering Faculty |
Palavras-Chave | #090609 Signal Processing #Filter Stability #Approximating Model #Modelling Error #Conditional Mean Estimate |
Tipo |
Conference Paper |