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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Liu, Y | - |
| dc.contributor.author | Wang, Z | - |
| dc.contributor.author | Hu, J | - |
| dc.contributor.author | Chen, Y | - |
| dc.contributor.author | Dong, H | - |
| dc.date.accessioned | 2025-12-04T12:38:04Z | - |
| dc.date.available | 2025-12-04T12:38:04Z | - |
| dc.date.issued | 2025-11-03 | - |
| dc.identifier | ORCiD: Yang Liu https://orcid.org/0000-0003-0253-0358 | - |
| dc.identifier | ORCiD: Zidong Wang https://orcid.org/0000-0002-9576-7401 | - |
| dc.identifier | ORCiD: Jun Hu https://orcid.org/0000-0002-7852-5064 | - |
| dc.identifier | ORCiD: Yun Chen https://orcid.org/0000-0002-9934-9979 | - |
| dc.identifier | ORCiD: Hongli Dong https://orcid.org/0000-0001-8531-6757 | - |
| dc.identifier | Article number: 103908 | - |
| dc.identifier.citation | Liu, Y. et al. (2025) 'Distributed maximum correntropy filtering for a class of multi-rate systems over sensor networks', Information Fusion, 127, 103908, pp. 1 - 11. doi: 10.1016/j.inffus.2025.103908. | en_US |
| dc.identifier.issn | 1566-2535 | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/32438 | - |
| dc.description | Data availability: Data sharing not applicable to this article as no datasets were generated or analyzed during the current study. | en_US |
| dc.description.abstract | In this paper, the distributed maximum correntropy filtering problem is investigated for a class of multi-rate systems over sensor networks. The system under consideration is monitored by a sensor network whose sensors are permitted to have different sampling periods. The maximum correntropy criterion is employed to handle the non-Gaussian noises effectively. Given the distributed nature and the asynchronous sampling of the sensor network, a novel filtering performance index based on the correntropy is constructed for each node in the sensor network. To maximize this correntropy-based index, the desired filter gain at each time step is calculated using a fixed-point algorithm. Sufficient conditions for ensuring the convergence of the fixed-point method are established. Finally, the efficacy of the proposed filtering scheme is demonstrated through a target tracking example. | en_US |
| dc.description.sponsorship | This work was supported in part by the National Natural Science Foundation of China under Grants 12471416, U22A2044, and U21A2019, in part by the Hainan Province Science and Technology Special Fund of China under Grant ZDYF2022SHFZ105, in part by the Royal Society of UK, and in part by the Alexander von Humboldt Foundation of Germany. | en_US |
| dc.format.extent | 1 - 11 | - |
| dc.language | English | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | Elsevier | en_US |
| dc.rights | Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International | - |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | - |
| dc.subject | sensor networks | en_US |
| dc.subject | distributed filtering | en_US |
| dc.subject | multi-rate systems | en_US |
| dc.subject | maximum correntropy criterion | en_US |
| dc.subject | non-Gaussian noises | en_US |
| dc.subject | fixed-point algorithm | en_US |
| dc.title | Distributed maximum correntropy filtering for a class of multi-rate systems over sensor networks | en_US |
| dc.type | Article | en_US |
| dc.date.dateAccepted | 2025-10-31 | - |
| dc.identifier.doi | https://doi.org/10.1016/j.inffus.2025.103908 | - |
| dc.relation.isPartOf | Information Fusion | - |
| pubs.publication-status | Published | - |
| pubs.volume | 127 | - |
| dc.identifier.eissn | 1872-6305 | - |
| dc.rights.license | https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.en | - |
| dcterms.dateAccepted | 2025-10-31 | - |
| dc.rights.holder | Elsevier B.V. | - |
| Appears in Collections: | Dept of Computer Science Embargoed Research Papers | |
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|---|---|---|---|---|
| FullText.pdf | Embargoed until 3 May 2027. Copyright © 2025 Elsevier B.V. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/ (see: https://www.elsevier.com/about/policies/sharing). | 493.22 kB | Adobe PDF | View/Open |
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