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Information Fusion over Network Dynamics with Unknown Correlations: An Overview
Wangyan Li1
Fuwen Yang2, *
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Submitted: 24 Oct 2022 | Accepted: 22 Nov 2022 | Published: 23 Jun 2023

Abstract

Unknown correlations (UCs) generally exist in a wide spectrum of practical multi-source information fusion problems, and thereby, their corresponding fusion problems have become one of the most important topics in information fusion domain. During the past three decades, the research on this topic has been growing rapidly and extensively, and, as a result, various important advances have been reported. In this overview, we intend to summarize the culmination of years of development in the field of information fusion under UCs as a roadmap. First, the potential reasons leading to UCs are investigated. According to the unknown nature of correlations, we further divide UCs into two categories, i.e., fully UCs, and partially UCs. For each category, the corresponding fusion methods are reviewed. Next, this roadmap witnesses the recent development of information fusion under UCs in a distributed way thanks to the popularity of distributed sensing technology. In particular, the distributed fusion techniques based on consensus, diffusion, and multi-object tracking strategies for UCs are examined. Finally, some future perspectives on information fusion under UCs are pointed out.

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How to Cite
Wangyan Li, & Fuwen Yang. (2023). Information Fusion over Network Dynamics with Unknown Correlations: An Overview. International Journal of Network Dynamics and Intelligence, 2(2), 100003. https://doi.org/10.53941/ijndi0201003
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