Xia Hong

159 papers receiving 2.6k citations

Peers

Xia Hong
Comparison fields: 5 of 155
  • Computational Mathematics 63
  • Control and Systems Engineering 964
  • Artificial Intelligence 1.1k
  • Signal Processing 238
  • Computer Vision and Pattern Recognition 390
Replace Mingjun Zhong with:
Mingjun Zhong China
Wenli Xu China
Marius Kloft Germany
Jing Zhao China
Michalis K. Titsias United Kingdom
Joaquin Quiñonero-Candela Germany
Jun Zhang China
Yuanyan Tang China
Hong Li China
Yu Cheng United States
Xia Hong relative to Mingjun Zhong China Mingjun Zhong's profile →
Citations per field
00.5×4.5×
Mingjun Zhong · 1×
Citations per year

Countries citing papers authored by Xia Hong

Since Specialization
Citations

This map shows the geographic impact of Xia Hong's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xia Hong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xia Hong more than expected).

Fields of papers citing papers by Xia Hong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xia Hong. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xia Hong. The network helps show where Xia Hong may publish in the future.

Co-authors

The 25 scholars most cited alongside Xia Hong, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xia Hong Line = papers co-authored together Xia Hong links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 170 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004220
2 2007141
3 2011110
4 2002107
5 2000105
6 200385
7 200276
8 201771
9 201069
10 200957
11 201653
12 200351
13 201451
14 200449
15 200249
16 201547
17 201741
18 201541
19 200740
20 202236

About Xia Hong

Xia Hong is a scholar working on Control and Systems Engineering, Artificial Intelligence, Computational Mechanics, Civil and Structural Engineering and Electrical and Electronic Engineering, having authored 170 papers that have together received 2.6k indexed citations. Recurring topics across this work include Control Systems and Identification (52 papers), Fault Detection and Control Systems (37 papers), Neural Networks and Applications (35 papers), Structural Health Monitoring Techniques (23 papers), Blind Source Separation Techniques (16 papers), Sparse and Compressive Sensing Techniques (15 papers), Advanced Adaptive Filtering Techniques (14 papers) and Fuzzy Logic and Control Systems (11 papers). The work is most often cited by research in Computational Mathematics (63 citations), Control and Systems Engineering (964 citations), Artificial Intelligence (1.1k citations), Signal Processing (238 citations) and Computer Vision and Pattern Recognition (390 citations). Xia Hong has collaborated with scholars based in United Kingdom, China and Saudi Arabia. Frequent co-authors include C.J. Harris, Sheng Chen, Paul Sharkey, Junbin Gao, Jingxin Zhang, Ming Gao, Yu Gong, Maoyin Chen, Richard Mitchell and John Q. Gan. Their work appears in journals such as Neurocomputing, International Journal of Systems Science, IEEE Transactions on Neural Networks and Learning Systems, International Journal of Women s Health and IEEE Transactions on Cybernetics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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