Non-linear Gaussian smoothing with Taylor moment expansion

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Authors

Date

2022

Department

Department of Electrical Engineering and Automation

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Mcode

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Language

en

Pages

5
80-84

Series

IEEE Signal Processing Letters, Volume 29

Abstract

This letter is concerned with solvingcontinuous-discrete Gaussian smoothing problems by using the Taylor moment expansion (TME) scheme. In the proposed smoothing method, we apply the TME method to approximate the transition density of the stochastic differential equation in the dynamic model. Furthermore, we derive a theoretical error bound (in the mean square sense) of the TME smoothing estimates showing that the smoother is stable under weak assumptions. Numerical experiments show that the proposed smoother outperforms a number of baseline smoothers.

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Tallennetaan OA-artikkeli, kun julkaistu

Keywords

Smoothing methods, Mathematical models, Signal processing algorithms, Numerical models, Approximation algorithms, Stochastic processes, Frequency modulation

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DOI

10.1109/LSP.2021.3125831

Citation

Zhao, Z & Särkkä, S 2022, ' Non-linear Gaussian smoothing with Taylor moment expansion ', IEEE Signal Processing Letters, vol. 29, 9606583, pp. 80-84 . https://doi.org/10.1109/LSP.2021.3125831

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https://urn.fi/URN:NBN:fi:aalto-202202091852

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[article-cris] Sähkötekniikan korkeakoulu / ELEC