Lijun Yang
- Biomedical Engineering
- Computational Mechanics top 10%
- Electrical and Electronic Engineering
- Cognitive Neuroscience
- Biomaterials
- Co-authors
- Feng ZhouXiaohui YangYuping WeiBin GuoGuodong ZhuYanbin ChenJie XuDebin Shan
- Topics
- EEG and Brain-Computer Interfaces (9 papers)Blind Source Separation Techniques (7 papers)Image and Signal Denoising Methods (5 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Lijun Yang
59 papers receiving 693 citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Biomedical Engineering 106
- Computational Mechanics 99
- Electrical and Electronic Engineering 93
- Cognitive Neuroscience 83
- Biomaterials 74
Countries citing papers authored by Lijun Yang
This map shows the geographic impact of Lijun 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 Lijun Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lijun Yang more than expected).
Fields of papers citing papers by Lijun Yang
This network shows the impact of papers produced by Lijun 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 Lijun Yang. The network helps show where Lijun Yang may publish in the future.
Co-authorship network of co-authors of Lijun Yang
This figure shows the co-authorship network connecting the top 25 collaborators of Lijun Yang. A scholar is included among the top collaborators of Lijun Yang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lijun Yang. Lijun Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 8 | |
| 3 | 2 | |
| 4 | 13 | |
| 5 | 12 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 9 | |
| 10 | 22 | |
| 11 | 12 | |
| 12 | 2 | |
| 13 | 7 | |
| 14 | 35 | |
| 15 | 10 | |
| 16 | 21 | |
| 17 | 2 | |
| 18 | 13 | |
| 19 | A New Hybrid Feature Extraction Method for Partial Discharge Signals Classification | 1 |
| 20 | Water Extract of The Lotus Leaf Suppressed Expression of Monocyte Chemoattractant Protein-1(MCP-1)and Vascular Cell Adhesion Molecule 1(VCAM-1)Induced By Oxidized Low Density Lipoprotein(Ox-LDL)in Human Umbilical Vein Endothelial Cells | 1 |
About Lijun Yang
Lijun Yang is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Computer Science Applications, having authored 68 papers that have together received 711 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (9 papers), Blind Source Separation Techniques (7 papers) and Image and Signal Denoising Methods (5 papers). The work is most often cited by research in Rehabilitation (53 citations), Molecular Medicine (36 citations) and Biomaterials (74 citations). Lijun Yang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Feng Zhou, Xiaohui Yang, Yuping Wei, Bin Guo, Guodong Zhu, Yanbin Chen, Jie Xu, Debin Shan, Jin Yang and Xi Chen. Their work appears in journals such as Analytical Chemistry, The Science of The Total Environment and Langmuir.
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.