Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/13272
Title: | A minimum variance filter for discrete time linear systems with parametric uncertainty |
Authors: | Allahyani, S Date, P |
Keywords: | Mathematical model;Noise measurement;Data models;Uncertainty;Biological system modeling;Numerical models;Additive noise |
Issue Date: | 2016 |
Publisher: | IEEE |
Citation: | The 24th Mediterranean Conference on Control and Automation, MED 2016, pp. 159 - 163, Athens, Greece, (21-24 June 2016) |
Abstract: | A minimum variance filter for a class of discrete time systems with additive as well as multiplicative noise is investigated in this paper. We extend the results from recent work by Ponomareva and Date to account for multiplicative noise in the measurement equation. More importantly, we provide an interpretation of the multiplicative noise in both transition and measurement equations in terms of parameter perturbations in a linear additive model. The utility of the proposed filtering algorithm is demonstrated through numerical simulation experiments using models from academic literature where the parameters are estimated from real data. |
URI: | http://ieeexplore.ieee.org/document/7535846/authors http://bura.brunel.ac.uk/handle/2438/13272 |
DOI: | http://dx.doi.org/10.1109/MED.2016.7535846 |
ISBN: | 9781467383455 |
Appears in Collections: | Dept of Mathematics Research Papers |
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