Da‐Zheng Feng
- Signal Processing top 1%
- Blind Source Separation Techniques 37
- Direction-of-Arrival Estimation Techniques 28
- Speech and Audio Processing 25
- Aerospace Engineering top 5%
- Radar Systems and Signal Processing 26
- Advanced SAR Imaging Techniques 20
- Computational Mechanics top 5%
- Advanced Adaptive Filtering Techniques 26
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- Face and Expression Recognition 11
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- Neural Networks and Applications 10
- Journals
- PLoS ONE (1 paper)Scientific Reports (2 papers)IEEE Transactions on Geoscience and Remote Sensing (1 paper)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Da‐Zheng Feng
111 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 84
- Signal Processing 553
- Aerospace Engineering 404
- Computational Mechanics 274
- Computer Vision and Pattern Recognition 225
- Computational Mathematics 5
Countries citing papers authored by Da‐Zheng Feng
This map shows the geographic impact of Da‐Zheng Feng'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 Da‐Zheng Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da‐Zheng Feng more than expected).
Fields of papers citing papers by Da‐Zheng Feng
This network shows the impact of papers produced by Da‐Zheng Feng. 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 Da‐Zheng Feng. The network helps show where Da‐Zheng Feng may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Da‐Zheng Feng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 6 | |
| 4 | 2022 | 0 | |
| 5 | 2021 | 4 | |
| 6 | 2020 | 3 | |
| 7 | 2017 | 23 | |
| 8 | 2016 | 4 | |
| 9 | 2016 | 3 | |
| 10 | 2015 | 1 | |
| 11 | 2015 | 14 | |
| 12 | 2014 | 11 | |
| 13 | 2011 | 3 | |
| 14 | 2009 | 12 | |
| 15 | Triply iterative algorithm for extracting statistically independent sources from array signals with noises | 2006 | 0 |
| 16 | 2006 | 4 | |
| 17 | 2005 | 22 | |
| 18 | 2004 | 19 | |
| 19 | 2001 | 11 | |
| 20 | 1998 | 108 |
About Da‐Zheng Feng
Da‐Zheng Feng is a scholar working on Signal Processing, Aerospace Engineering and Computer Vision and Pattern Recognition, having authored 120 papers that have together received 1.1k indexed citations. Recurring topics across this work include Blind Source Separation Techniques (37 papers), Direction-of-Arrival Estimation Techniques (28 papers), Advanced Adaptive Filtering Techniques (26 papers), Radar Systems and Signal Processing (26 papers), Speech and Audio Processing (25 papers), Advanced SAR Imaging Techniques (20 papers), Face and Expression Recognition (11 papers) and Neural Networks and Applications (10 papers). The work is most often cited by research in Signal Processing (553 citations), Aerospace Engineering (404 citations) and Computational Mechanics (274 citations). Da‐Zheng Feng has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Zheng Bao, Wei Xing Zheng, Licheng Jiao, Hongwei Liu, Jin Li, Yongbo Zhao, Xie Hu, Xian‐Da Zhang, Yan Zhou and Bingbing Li. Their work appears in journals such as PLoS ONE, Scientific Reports and IEEE Transactions on Geoscience and Remote Sensing.
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.