Jigen Peng
Impact in
- Modeling and Simulation top 1%
- Fractional Differential Equations Solutions
- Numerical Analysis top 5%
Papers in
-
- Sparse and Compressive Sensing Techniques 24
- Co-authors
- Shigang Yue (21 shared papers)Hongxin Wang (11 shared papers)Kexue Li (3 shared papers)Bo Huang (1 shared paper)Zongben Xu (1 shared paper)Huihui Song (1 shared paper)Junxiong Jia (12 shared papers)Qinbing Fu (21 shared papers)
- Journals
- Neural Networks (6 papers)IEEE Access (5 papers)IEEE Transactions on Neural Networks and Learning Systems (5 papers)Neurocomputing (4 papers)Journal of Computational and Applied Mathematics (3 papers)
- Partner nations
- ChinaUnited KingdomHong Kong
In The Last Decade
Jigen Peng
112 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 86
- Modeling and Simulation 216
- Numerical Analysis 139
- Media Technology 187
- Applied Mathematics 188
- Computer Vision and Pattern Recognition 306
Countries citing papers authored by Jigen Peng
This map shows the geographic impact of Jigen Peng'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 Jigen Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jigen Peng more than expected).
Fields of papers citing papers by Jigen Peng
This network shows the impact of papers produced by Jigen Peng. 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 Jigen Peng. The network helps show where Jigen Peng may publish in the future.
Co-authors
The 25 scholars most cited alongside Jigen Peng, 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 121 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 182 | |
| 2 | 2018 | 51 | |
| 3 | 2010 | 47 | |
| 4 | 2019 | 44 | |
| 5 | 2019 | 42 | |
| 6 | 2011 | 29 | |
| 7 | 2019 | 25 | |
| 8 | 2017 | 24 | |
| 9 | 2012 | 23 | |
| 10 | 2021 | 22 | |
| 11 | 2020 | 21 | |
| 12 | 2021 | 21 | |
| 13 | 2018 | 20 | |
| 14 | 2015 | 20 | |
| 15 | 2015 | 18 | |
| 16 | 2017 | 17 | |
| 17 | 2022 | 17 | |
| 18 | 2010 | 16 | |
| 19 | 2015 | 16 | |
| 20 | 2013 | 14 |
About Jigen Peng
Jigen Peng is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Cognitive Neuroscience, Numerical Analysis and Applied Mathematics, having authored 121 papers that have together received 1.0k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (24 papers), Neural dynamics and brain function (18 papers), Fractional Differential Equations Solutions (17 papers), Neurobiology and Insect Physiology Research (15 papers), Advanced Optimization Algorithms Research (14 papers), Nonlinear Differential Equations Analysis (14 papers), Optimization and Variational Analysis (13 papers) and Advanced Memory and Neural Computing (11 papers). The work is most often cited by research in Modeling and Simulation (216 citations), Numerical Analysis (139 citations), Media Technology (187 citations), Applied Mathematics (188 citations) and Computer Vision and Pattern Recognition (306 citations). Jigen Peng has collaborated with scholars based in China, United Kingdom and Hong Kong. Frequent co-authors include Shigang Yue, Hongxin Wang, Kexue Li, Bo Huang, Zongben Xu, Huihui Song, Junxiong Jia, Qinbing Fu, Haiyang Li and Yuchao Tang. Their work appears in journals such as Neural Networks, IEEE Access, IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing and Journal of Computational and Applied Mathematics.
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.