Information Fusion over Network Dynamics with Unknown Correlations: An Overview

信息融合 人气 计算机科学 领域(数学) 传感器融合 融合 数据科学 人工智能 心理学 数学 语言学 社会心理学 哲学 纯数学
作者
Wangyan Li,Fuwen Yang
出处
期刊: 卷期号:: 100003-100003 被引量:58
标识
DOI:10.53941/ijndi0201003
摘要

Survey/review study Information Fusion over Network Dynamics with Unknown Correlations: An Overview Wangyan Li 1, and Fuwen Yang 2,* 1 College of Science, University of Shanghai for Science and Technology, Shanghai 200093, China 2 Griffth School of Engineering, Griffth University, Gold Coast Campus, QLD 4222, Australia * Correspondence: fuwen.yang@griffth.edu.au Received: 24 October 2022 Accepted: 22 November 2022 Published: 23 June 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.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
领导范儿应助栗子乳酪采纳,获得10
2秒前
禹平露发布了新的文献求助10
2秒前
2秒前
逍遥发布了新的文献求助10
3秒前
傲娇元霜发布了新的文献求助10
3秒前
4秒前
4秒前
龙2024发布了新的文献求助10
4秒前
完美世界应助OK采纳,获得10
5秒前
快乐灵安完成签到,获得积分10
5秒前
6秒前
Thea发布了新的文献求助30
6秒前
txyilearning发布了新的文献求助10
6秒前
7秒前
Zachary发布了新的文献求助10
7秒前
7秒前
赘婿应助傲娇元霜采纳,获得10
8秒前
PINGGUO发布了新的文献求助10
8秒前
东郭秋凌发布了新的文献求助20
9秒前
热爱就值得完成签到,获得积分20
10秒前
99完成签到 ,获得积分10
11秒前
瘦瘦乌龟发布了新的文献求助30
12秒前
molihuakai应助果冻采纳,获得10
12秒前
13秒前
11完成签到,获得积分10
13秒前
毛毛不烦发布了新的文献求助10
14秒前
贪玩的秋柔应助ertredffg采纳,获得30
14秒前
15秒前
kiara完成签到,获得积分20
15秒前
doctc发布了新的文献求助10
16秒前
16秒前
16秒前
顾矜应助rosalieshi采纳,获得10
17秒前
焜少完成签到,获得积分10
17秒前
彭于晏应助asdfqwer采纳,获得10
17秒前
等风寻梦完成签到,获得积分10
17秒前
活力橘子发布了新的文献求助30
18秒前
大个应助BellaDanDan采纳,获得10
19秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Navigating Normative Orders. Interdisciplinary Perspectives 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7761176
求助须知:如何正确求助?哪些是违规求助? 9306306
关于积分的说明 20293825
捐赠科研通 7345833
什么是DOI,文献DOI怎么找? 3313115
关于科研通互助平台的介绍 2463387
邀请新用户注册赠送积分活动 2327326