Jun Wang
Impact in
- Computer Networks and Communications top 0.02%
- Neural Networks Stability and Synchronization
- Distributed Control Multi-Agent Systems
- Control and Systems Engineering top 0.02%
- Adaptive Control of Nonlinear Systems
- Robotic Mechanisms and Dynamics
- Stability and Control of Uncertain Systems
Papers in
-
- Neural Networks and Applications 227
- Metaheuristic Optimization Algorithms Research 61
-
- Adaptive Control of Nonlinear Systems 61
- Robotic Mechanisms and Dynamics 51
- Fault Detection and Control Systems 49
- Co-authors
- Qingshan Liu (30 shared papers)Zhouhua Peng (22 shared papers)Zhigang Zeng (30 shared papers)Youshen Xia (30 shared papers)Zheng Yan (25 shared papers)Jinde Cao (9 shared papers)Qing‐Long Han (19 shared papers)Yunong Zhang (11 shared papers)
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (59 papers)Neural Networks (46 papers)IEEE Transactions on Systems Man and Cybernetics Systems (20 papers)IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) (12 papers)IEEE Transactions on Industrial Electronics (10 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Jun Wang
954 papers receiving 36.3k citations
Jun Wang's Hit Papers
Peers
Comparison fields: 5 of 215
- Computer Networks and Communications 13.2k
- Control and Systems Engineering 12.0k
- Statistical and Nonlinear Physics 4.7k
- Artificial Intelligence 12.3k
- Computer Vision and Pattern Recognition 4.0k
Countries citing papers authored by Jun Wang
This map shows the geographic impact of Jun Wang'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 Jun Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Wang more than expected).
Fields of papers citing papers by Jun Wang
This network shows the impact of papers produced by Jun Wang. 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 Jun Wang. The network helps show where Jun Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 1.0k papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Introduction to artificial neural systems Hit paper breakdown → | 1992 | 1699 |
| 2 | A recurrent neural network for solving Sylvester equation with time-varying coefficients Hit paper breakdown → | 2002 | 548 |
| 3 | An Overview of Recent Advances in Coordinated Control of Multiple Autonomous Surface Vehicles Hit paper breakdown → | 2020 | 523 |
| 4 | 2003 | 448 | |
| 5 | Secure State Estimation and Control of Cyber-Physical Systems: A Survey Hit paper breakdown → | 2020 | 445 |
| 6 | Global asymptotic and robust stability of recurrent neural networks with time delays Hit paper breakdown → | 2005 | 428 |
| 7 | Efficient Architecture Search by Network Transformation Hit paper breakdown → | 2018 | 329 |
| 8 | Distributed Maneuvering of Autonomous Surface Vehicles Based on Neurodynamic Optimization and Fuzzy Approximation Hit paper breakdown → | 2017 | 323 |
| 9 | Output-Feedback Path-Following Control of Autonomous Underwater Vehicles Based on an Extended State Observer and Projection Neural Networks Hit paper breakdown → | 2017 | 315 |
| 10 | Global Stability of Complex-Valued Recurrent Neural Networks With Time-Delays Hit paper breakdown → | 2012 | 313 |
| 11 | Reliable asynchronous sampled-data filtering of T–S fuzzy uncertain delayed neural networks with stochastic switched topologies Hit paper breakdown → | 2018 | 312 |
| 12 | Designing routing metrics for mesh networks | 2005 | 307 |
| 13 | A Second-Order Multi-Agent Network for Bound-Constrained Distributed Optimization Hit paper breakdown → | 2015 | 306 |
| 14 | 2017 | 290 | |
| 15 | 2002 | 283 | |
| 16 | 2012 | 281 | |
| 17 | 2011 | 276 | |
| 18 | Multivariate Temporal Convolutional Network: A Deep Neural Networks Approach for Multivariate Time Series Forecasting Hit paper breakdown → | 2019 | 255 |
| 19 | 2005 | 255 | |
| 20 | 2003 | 254 |
About Jun Wang
Jun Wang is a scholar working on Artificial Intelligence, Control and Systems Engineering, Computer Networks and Communications, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, having authored 1.0k papers that have together received 37.2k indexed citations. Recurring topics across this work include Neural Networks and Applications (227 papers), Neural Networks Stability and Synchronization (135 papers), Advanced Memory and Neural Computing (80 papers), Metaheuristic Optimization Algorithms Research (61 papers), Adaptive Control of Nonlinear Systems (61 papers), Distributed Control Multi-Agent Systems (58 papers), Robotic Mechanisms and Dynamics (51 papers) and Fault Detection and Control Systems (49 papers). The work is most often cited by research in Computer Networks and Communications (13.2k citations), Control and Systems Engineering (12.0k citations), Statistical and Nonlinear Physics (4.7k citations), Artificial Intelligence (12.3k citations) and Computer Vision and Pattern Recognition (4.0k citations). Jun Wang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Qingshan Liu, Zhouhua Peng, Zhigang Zeng, Youshen Xia, Zheng Yan, Jinde Cao, Qing‐Long Han, Yunong Zhang, Zhenyuan Guo and Shaofu Yang. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Neural Networks, IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) and IEEE Transactions on Industrial Electronics.
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.