Dedong Yang

1.1k citations
46 papers · 810 · h-index 12

Impact in

Papers in

Dedong Yang

45 papers receiving 777 citations

Peers

Dedong Yang
Comparison fields: 5 of 84
  • Control and Systems Engineering 489
  • Computer Networks and Communications 291
  • Experimental and Cognitive Psychology 91
  • Computer Vision and Pattern Recognition 130
  • Computational Theory and Mathematics 64
Replace Aiping Wang with:
Aiping Wang China
Yanqing Liu China
Robert Murphey United States
C.C. Ko Singapore
Νικόλαος Παππάς Sweden
Deqiang Ouyang China
Mayank Sharma India
Tejas D. Kulkarni United States
Jingchao Sun China
George F. Fragulis Greece
Dedong Yang relative to Aiping Wang China Aiping Wang's profile →
Citations per field
00.5×3.5×
Aiping Wang · 1×
Citations per year

Countries citing papers authored by Dedong Yang

Since Specialization
Citations

This map shows the geographic impact of Dedong Yang'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 Dedong Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dedong Yang more than expected).

Fields of papers citing papers by Dedong Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dedong Yang. 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 Dedong Yang. The network helps show where Dedong Yang may publish in the future.

Co-authors

The 25 scholars most cited alongside Dedong Yang, 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 Dedong Yang Line = papers co-authored together Dedong Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007169
2 2018161
3 2009116
4 200835
5 202130
6 201030
7 202018
8 200917
9 201014
10 200713
11 199613
12 202212
13 201911
14 201911
15 202211
16 202111
17 201010
18 20219
19 20239
20 20239

About Dedong Yang

Dedong Yang is a scholar working on Control and Systems Engineering, Computer Networks and Communications, Computer Vision and Pattern Recognition, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 46 papers that have together received 810 indexed citations. Recurring topics across this work include Stability and Control of Uncertain Systems (25 papers), Neural Networks Stability and Synchronization (17 papers), Distributed Control Multi-Agent Systems (10 papers), Adaptive Control of Nonlinear Systems (7 papers), Advanced Neural Network Applications (4 papers), Chaos control and synchronization (3 papers), Iterative Learning Control Systems (3 papers) and Fault Detection and Control Systems (3 papers). The work is most often cited by research in Control and Systems Engineering (489 citations), Computer Networks and Communications (291 citations), Experimental and Cognitive Psychology (91 citations), Computer Vision and Pattern Recognition (130 citations) and Computational Theory and Mathematics (64 citations). Dedong Yang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Huaguang Zhang, Tianyou Chai, Kai‐Yuan Cai, Abeer Alsadoon, Ashutosh Kumar Singh, Amr Elchouemi, P. W. C. Prasad, Huaguang Zhang, Jun Yang and Ming Li. Their work appears in journals such as IET Control Theory and Applications, The Visual Computer, International Journal of Systems Science, Measurement and Biomedical Signal Processing and Control.

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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