Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/14087
Title: A minimum variance filter for continuous discrete systems with additive-multiplicative noise
Authors: Allahyani, S
Date, P
Keywords: Mathematical model;Time measurement;Covariance matrices;Noise measurement;Bayes methods
Issue Date: 2016
Publisher: IEEE
Citation: 24th European Signal Processing Conference (EUSIPCO), Budapest, Hungary, 29 August - 2 September, (2016)
Abstract: In this paper, we extend the minimum variance filter, which is proposed in the literature for discrete state space systems with multiplicative noise, to continuous-discrete systems with multiplicative noise. The differential equations that describe the process are discretised using the Euler scheme at a higher sampling frequency than the measurement frequency. We test the performance of our new filter i.e. continuous discrete filter (CDF) on simulated numerical examples and compare the results with discrete discrete filter (DDF) which ignores the state behaviour in-between the measurement samples. The results show that the CDF outperforms the DDF in all the cases examined.
URI: http://bura.brunel.ac.uk/handle/2438/14087
DOI: http://dx.doi.org/10.1109/EUSIPCO.2016.7760665
ISSN: 2219-5491
Appears in Collections:Dept of Mathematics Research Papers

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