Feiran Yang

1.1k citations
74 papers · 745 · h-index 16

Impact in

Papers in

Feiran Yang

70 papers receiving 730 citations

Peers

Feiran Yang
Comparison fields: 5 of 46
  • Signal Processing 598
  • Computational Mechanics 557
  • Cognitive Neuroscience 83
  • Biomedical Engineering 185
  • Computer Vision and Pattern Recognition 63
Replace Asutosh Kar with:
Asutosh Kar India
Márcio Holsbach Costa Brazil
Takanobu Nishiura Japan
Gerald Enzner Germany
Yoichi Haneda Japan
Liming Shi China
Alexandre Guérin France
Yutaka Kaneda Japan
Sebastian Braun United States
Gema Piñero Spain
Feiran Yang relative to Asutosh Kar India Asutosh Kar's profile →
Citations per field
00.5×1.5×2.3×
Asutosh Kar · 1×
Citations per year

Countries citing papers authored by Feiran Yang

Since Specialization
Citations

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

Fields of papers citing papers by Feiran Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201881
2 202076
3 201235
4 201734
5 201831
6 201923
7 201723
8 202221
9 201221
10 201920
11 201420
12 201520
13 201319
14 201517
15 201815
16 202215
17 202214
18 201914
19 201513
20 202313

About Feiran Yang

Feiran Yang is a scholar working on Signal Processing, Computational Mechanics, Computer Vision and Pattern Recognition, Biomedical Engineering and Artificial Intelligence, having authored 74 papers that have together received 745 indexed citations. Recurring topics across this work include Speech and Audio Processing (66 papers), Advanced Adaptive Filtering Techniques (52 papers), Blind Source Separation Techniques (33 papers), Acoustic Wave Phenomena Research (11 papers), Music and Audio Processing (10 papers), Speech Recognition and Synthesis (7 papers), Hearing Loss and Rehabilitation (6 papers) and Music Technology and Sound Studies (5 papers). The work is most often cited by research in Signal Processing (598 citations), Computational Mechanics (557 citations), Cognitive Neuroscience (83 citations), Biomedical Engineering (185 citations) and Computer Vision and Pattern Recognition (63 citations). Feiran Yang has collaborated with scholars based in China, Germany and United Kingdom. Frequent co-authors include Jun Yang, Ming Wu, Gerald Enzner, Felix Albu, Yin Cao, Peifeng Ji, Ming Wu, Rui Zhu, Junfeng Li and Ming Wu. Their work appears in journals such as IEEE Signal Processing Letters, IEEE/ACM Transactions on Audio Speech and Language Processing, The Journal of the Acoustical Society of America, Applied Acoustics and Signal Processing.

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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