Copula-based convolution for fast point-mass prediction

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43962834" target="_blank" >RIV/49777513:23520/22:43962834 - isvavai.cz</a>
Result on the web
<a href="https://dy.doi.org/10.1016/j.sigpro.2021.108367" target="_blank" >https://dy.doi.org/10.1016/j.sigpro.2021.108367</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.sigpro.2021.108367" target="_blank" >10.1016/j.sigpro.2021.108367</a>

Result language
angličtina
Original language name
Copula-based convolution for fast point-mass prediction
Original language description
This paper deals with the state estimation of the nonlinear stochastic dynamic discrete-in-time models by a numerical solution to the Bayesian recursive relations represented by the point-mass filter (PMF). In particular, emphasis is placed on the development of the fast convolution, which reduces computational complexity of the PMF prediction step by the orders of magnitude for models with a diagonal form of the dynamic equation. The copula-based convolution decomposes the joint conditional density into the marginal densities (allowing efficient prediction) and an easy-to-calculate copula density function. As a consequence, it has the linear growth of its computational complexity with the state dimension, which is in a contrast with the exponential growth of the standard convolution complexity in PMF methods. The proposed fast convolution is analysed and illustrated in a numerical study for a static example and a dynamic terrain-aided navigation scenario. An exemplary implementation of the proposed convolution is provided along with the paper.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20205 - Automation and control systems

Project
<a href="/en/project/GC20-06054J" target="_blank" >GC20-06054J: Intelligent Distributed Estimation Architectures</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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