Fabing Duan

1.4k total citations
62 papers, 1.2k citations indexed

About

Fabing Duan is a scholar working on Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty and Computer Networks and Communications. According to data from OpenAlex, Fabing Duan has authored 62 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Statistical and Nonlinear Physics, 24 papers in Statistics, Probability and Uncertainty and 18 papers in Computer Networks and Communications. Recurrent topics in Fabing Duan's work include stochastic dynamics and bifurcation (48 papers), Probabilistic and Robust Engineering Design (24 papers) and Diffusion and Search Dynamics (15 papers). Fabing Duan is often cited by papers focused on stochastic dynamics and bifurcation (48 papers), Probabilistic and Robust Engineering Design (24 papers) and Diffusion and Search Dynamics (15 papers). Fabing Duan collaborates with scholars based in China, Australia and France. Fabing Duan's co-authors include Derek Abbott, François Chapeau‐Blondeau, Bohou Xu, Jianlong Li, Ronghao Bao, Yan Pan, David Rousseau, Yu Hen Hu, Hon Keung Tony Ng and Limin Luo and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Transactions on Signal Processing.

In The Last Decade

Fabing Duan

60 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Fabing Duan China 19 896 413 353 307 181 62 1.2k
Sanya Mitaim United States 11 480 0.5× 178 0.4× 165 0.5× 117 0.4× 211 1.2× 26 792
Steeve Zozor France 16 412 0.5× 136 0.3× 136 0.4× 135 0.4× 110 0.6× 48 876
J.H. Michels United States 19 271 0.3× 137 0.3× 298 0.8× 82 0.3× 51 0.3× 64 1.4k
R. Yamapi Cameroon 18 777 0.9× 35 0.1× 649 1.8× 55 0.2× 149 0.8× 72 978
Donatello Materassi United States 12 126 0.1× 26 0.1× 103 0.3× 174 0.6× 74 0.4× 68 628
Stefan Klus Germany 11 454 0.5× 153 0.4× 16 0.0× 96 0.3× 16 0.1× 30 677
Alexandre Mauroy Belgium 10 375 0.4× 113 0.3× 138 0.4× 40 0.1× 57 0.3× 34 536
Michael Schanz Germany 20 604 0.7× 9 0.0× 304 0.9× 35 0.1× 67 0.4× 52 1.0k
Piotr Kowalczyk Poland 12 814 0.9× 19 0.0× 390 1.1× 30 0.1× 72 0.4× 28 1.6k
A. Venkatesan India 18 843 0.9× 12 0.0× 680 1.9× 25 0.1× 158 0.9× 36 1.1k

Countries citing papers authored by Fabing Duan

Since Specialization
Citations

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

Fields of papers citing papers by Fabing Duan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fabing Duan

This figure shows the co-authorship network connecting the top 25 collaborators of Fabing Duan. A scholar is included among the top collaborators of Fabing Duan 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 Fabing Duan. Fabing Duan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
An, Cuixia, Fabing Duan, François Chapeau‐Blondeau, & Derek Abbott. (2025). Exploring the Bayes-oriented noise injection approach in neural networks. Physics Letters A. 555. 130804–130804.
2.
Duan, Fabing, et al.. (2024). Self-gating stochastic-resonance-based autoencoder for unsupervised learning. Physical review. E. 110(1). 14107–14107. 3 indexed citations
3.
Duan, Fabing, et al.. (2022). Generalization of stochastic-resonance-based threshold networks with Tikhonov regularization. Physical review. E. 106(1). L012101–L012101. 14 indexed citations
4.
Duan, Fabing, et al.. (2022). Training threshold neural networks by extreme learning machine and adaptive stochastic resonance. Physics Letters A. 432. 128008–128008. 5 indexed citations
5.
Yang, Zhongshan, et al.. (2022). Optimal added noise for minimizing distortion in quantizer-array linear estimation. Chaos Solitons & Fractals. 166. 112887–112887. 2 indexed citations
6.
Duan, Fabing, et al.. (2022). Adaptive stochastic resonance based convolutional neural network for image classification. Chaos Solitons & Fractals. 162. 112429–112429. 17 indexed citations
7.
Li, Fei, Fabing Duan, François Chapeau‐Blondeau, & Derek Abbott. (2021). Signal estimation and filtering from quantized observations via adaptive stochastic resonance. Physical review. E. 103(5). 52108–52108. 13 indexed citations
8.
Dong, Peng, Fabing Duan, & Kai Wang. (2019). Intelligent Nano-Ground Based on Triboelctric Nanogenerator for Motion Tracking. 217–221. 1 indexed citations
9.
Pan, Yan, et al.. (2017). Exploiting vibrational resonance in weak-signal detection. Physical review. E. 96(2). 22141–22141. 31 indexed citations
10.
Duan, Fabing, François Chapeau‐Blondeau, & Derek Abbott. (2016). Capacity of very noisy communication channels based on Fisher information. Scientific Reports. 6(1). 27946–27946. 7 indexed citations
11.
Duan, Fabing, et al.. (2016). Optimal weighted suprathreshold stochastic resonance with multigroup saturating sensors. Physica A Statistical Mechanics and its Applications. 457. 348–355. 11 indexed citations
12.
Duan, Fabing, François Chapeau‐Blondeau, & Derek Abbott. (2014). Double-maximum enhancement of signal-to-noise ratio gain via stochastic resonance and vibrational resonance. Physical Review E. 90(2). 22134–22134. 18 indexed citations
13.
Duan, Fabing, François Chapeau‐Blondeau, & Derek Abbott. (2014). Stochastic Resonance with Colored Noise for Neural Signal Detection. PLoS ONE. 9(3). e91345–e91345. 17 indexed citations
14.
Ma, Yumei, Fabing Duan, François Chapeau‐Blondeau, & Derek Abbott. (2013). Weak-Periodic Stochastic Resonance in a Parallel Array of Static Nonlinearities. PLoS ONE. 8(3). e58507–e58507. 6 indexed citations
15.
Duan, Fabing, François Chapeau‐Blondeau, & Derek Abbott. (2012). Fisher Information as a Metric of Locally Optimal Processing and Stochastic Resonance. PLoS ONE. 7(4). e34282–e34282. 14 indexed citations
16.
Ng, Hon Keung Tony, Limin Luo, Yu Hen Hu, & Fabing Duan. (2011). Parameter estimation of three-parameter Weibull distribution based on progressively Type-II censored samples. Journal of Statistical Computation and Simulation. 82(11). 1661–1678. 80 indexed citations
17.
Chapeau‐Blondeau, François, Fabing Duan, & Derek Abbott. (2010). Synaptic signal transduction aided by noise in a dynamical saturating model. Physical Review E. 81(2). 21124–21124. 9 indexed citations
18.
Duan, Fabing, François Chapeau‐Blondeau, & Derek Abbott. (2006). Noise-enhanced SNR gain in parallel array of bistable oscillators. Electronics Letters. 42(17). 1008–1009. 30 indexed citations
19.
Xu, Bohou, Fabing Duan, & François Chapeau‐Blondeau. (2004). Comparison of aperiodic stochastic resonance in a bistable system realized by adding noise and by tuning system parameters. Physical Review E. 69(6). 61110–61110. 59 indexed citations
20.
Rousseau, David, Fabing Duan, & François Chapeau‐Blondeau. (2003). Suprathreshold stochastic resonance and noise-enhanced Fisher information in arrays of threshold devices. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 68(3). 31107–31107. 53 indexed citations

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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