Ji-Nan Lin

677 citations
38 papers · 484 · h-index 13

Impact in

Papers in

Ji-Nan Lin

32 papers receiving 455 citations

Peers

Ji-Nan Lin
Comparison fields: 5 of 69
  • Signal Processing 113
  • Control and Systems Engineering 148
  • Statistical and Nonlinear Physics 73
  • Computer Vision and Pattern Recognition 113
  • Computational Mechanics 91
Replace Shengyang Luan with:
Shengyang Luan China
Riadh Ksantini Canada
Grigorios Tzortzis Greece
Serguei Primak Canada
Linyu Peng China
H. Tokumaru Japan
Jacek Ilow Canada
Yixian Yang China
Chris Darken United States
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Citations per field
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Shengyang Luan · 1×
Citations per year

Countries citing papers authored by Ji-Nan Lin

Since Specialization
Citations

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

Fields of papers citing papers by Ji-Nan Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ji-Nan Lin. 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 Ji-Nan Lin. The network helps show where Ji-Nan Lin may publish in the future.

Co-authors

The 7 scholars most cited alongside Ji-Nan Lin, 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 Ji-Nan Lin Line = papers co-authored together Ji-Nan Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199280
2 199051
3 199444
4 199534
5 199331
6 199231
7 201626
8 201622
9 201517
10 199215
11 199314
12 201614
13 201612
14 199310
15 202010
16 19929
17 20149
18 20159
19 20178
20 19948

About Ji-Nan Lin

Ji-Nan Lin is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Computational Mechanics, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 38 papers that have together received 484 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (14 papers), Advanced Adaptive Filtering Techniques (11 papers), Image and Signal Denoising Methods (11 papers), Neural Networks and Applications (11 papers), Complex Network Analysis Techniques (6 papers), Control Systems and Identification (5 papers), Complex Systems and Time Series Analysis (5 papers) and Structural Health Monitoring Techniques (4 papers). The work is most often cited by research in Signal Processing (113 citations), Control and Systems Engineering (148 citations), Statistical and Nonlinear Physics (73 citations), Computer Vision and Pattern Recognition (113 citations) and Computational Mechanics (91 citations). Ji-Nan Lin has collaborated with scholars based in Germany, China and Hong Kong. Frequent co-authors include R. Unbehauen, Can-Zhong Yao, Xiaofeng Liu, Xiaofeng Liu, Wenzhe Li, Yen‐Sheng Chen and Bo‐Lin Lin. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Electronics Letters, IEEE Transactions on Antennas and Propagation, Fractals and Neural Computation.

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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