Sufficiently informative measurements for stability of approximate conditional mean estimates


Autoria(s): Techakesari, Onvaree; Ford, Jason J.
Data(s)

15/11/2012

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

http://eprints.qut.edu.au/53898/

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