Renyu Ye

481 total citations
21 papers, 387 citations indexed

About

Renyu Ye is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics and Artificial Intelligence. According to data from OpenAlex, Renyu Ye has authored 21 papers receiving a total of 387 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Networks and Communications, 11 papers in Statistical and Nonlinear Physics and 10 papers in Artificial Intelligence. Recurrent topics in Renyu Ye's work include Neural Networks Stability and Synchronization (19 papers), Neural Networks and Applications (10 papers) and stochastic dynamics and bifurcation (9 papers). Renyu Ye is often cited by papers focused on Neural Networks Stability and Synchronization (19 papers), Neural Networks and Applications (10 papers) and stochastic dynamics and bifurcation (9 papers). Renyu Ye collaborates with scholars based in China, United States and South Korea. Renyu Ye's co-authors include Hai Zhang, Jinde Cao, Xiaodi Li, Ivanka Stamova, Xinsheng Liu, Ahmed Alsaedi, Ahmad Alsaedi, Ying Wan, Ahmed Alsaedi and Chen Wang and has published in prestigious journals such as Scientific Reports, Journal of the Franklin Institute and Physica A Statistical Mechanics and its Applications.

In The Last Decade

Renyu Ye

19 papers receiving 381 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Renyu Ye China 11 299 192 164 72 65 21 387
C. Sowmiya India 12 315 1.1× 134 0.7× 129 0.8× 46 0.6× 80 1.2× 17 403
C. Maharajan India 12 273 0.9× 123 0.6× 123 0.8× 49 0.7× 81 1.2× 16 375
Huaiqin Wu China 7 328 1.1× 208 1.1× 113 0.7× 45 0.6× 58 0.9× 11 389
Qinghua Zhou China 13 429 1.4× 231 1.2× 249 1.5× 26 0.4× 83 1.3× 53 508
Hao Yin China 8 151 0.5× 133 0.7× 111 0.7× 52 0.7× 47 0.7× 21 417
Yajuan Gu China 9 311 1.0× 249 1.3× 128 0.8× 57 0.8× 101 1.6× 13 373
Xianyun Xu China 9 287 1.0× 166 0.9× 83 0.5× 30 0.4× 62 1.0× 19 365
Vijay K. Yadav India 15 346 1.2× 358 1.9× 84 0.5× 32 0.4× 37 0.6× 41 468
Zhilong He China 12 224 0.7× 150 0.8× 57 0.3× 28 0.4× 50 0.8× 29 326
Trayan Stamov Bulgaria 10 226 0.8× 138 0.7× 84 0.5× 52 0.7× 36 0.6× 22 327

Countries citing papers authored by Renyu Ye

Since Specialization
Citations

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

Fields of papers citing papers by Renyu Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Renyu Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Renyu Ye. A scholar is included among the top collaborators of Renyu Ye 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 Renyu Ye. Renyu Ye 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.
Zhang, Hai, et al.. (2025). Fixed/Predefined time synchronization of fractional quaternion delayed neural networks with disturbances. Mathematics and Computers in Simulation. 232. 276–294. 1 indexed citations
2.
Ye, Renyu, et al.. (2024). Finite-time synchronization criteria on delayed FOCVNNs with uncertain parameters and difference operator. Journal of the Franklin Institute. 361(12). 107017–107017. 2 indexed citations
3.
4.
Ye, Renyu, et al.. (2024). Novel Adaptive Pinning Synchronization Criteria for Delayed Caputo-type Fuzzy Neural Networks With Uncertain Parameters. International Journal of Control Automation and Systems. 22(9). 2942–2953. 1 indexed citations
5.
Zhang, Hai, Chen Wang, Renyu Ye, Ivanka Stamova, & Jinde Cao. (2023). Novel order-dependent passivity conditions of fractional generalized Cohen–Grossberg neural networks with proportional delays. Communications in Nonlinear Science and Numerical Simulation. 120. 107155–107155. 21 indexed citations
6.
Zhang, Hai, et al.. (2023). Quasi-projective synchronization analysis of discrete-time FOCVNNs via delay-feedback control. Chaos Solitons & Fractals. 173. 113629–113629. 17 indexed citations
7.
Zhang, Hai, et al.. (2023). Quasi-uniform synchronization of fractional fuzzy discrete-time delayed neural networks via delayed feedback control design. Communications in Nonlinear Science and Numerical Simulation. 126. 107507–107507. 14 indexed citations
8.
Ye, Renyu, et al.. (2023). Asymptotic stability and quantitative synchronization of fractional competitive neural networks with multiple restrictions. Mathematics and Computers in Simulation. 217. 338–353. 10 indexed citations
9.
Zhang, Hai, et al.. (2023). Finite time passivity analysis for Caputo fractional BAM reaction–diffusion delayed neural networks. Mathematics and Computers in Simulation. 208. 424–443. 11 indexed citations
10.
Zhang, Hai, et al.. (2023). Laplace transform and nonlinear control design for quasi‐projective synchronization for Caputo inertial delayed neural networks. Mathematical Methods in the Applied Sciences. 46(16). 16483–16499.
11.
Zhang, Hai, et al.. (2023). Adaptive quasi-synchronization analysis for Caputo delayed Cohen–Grossberg neural networks. Mathematics and Computers in Simulation. 212. 49–65. 10 indexed citations
12.
Zhang, Hai, et al.. (2023). Quasi-projective Synchronization Analysis of Delayed Caputo-Type BAM Neural Networks in the Complex Field. Neural Processing Letters. 55(6). 7469–7492. 3 indexed citations
13.
14.
Ye, Renyu & Xinsheng Liu. (2020). How the known reference weakens the visual oblique effect: a Bayesian account of cognitive improvement by cue influence. Scientific Reports. 10(1). 20269–20269. 3 indexed citations
15.
Zhang, Hai, et al.. (2018). Synchronization stability of Riemann–Liouville fractional delay-coupled complex neural networks. Physica A Statistical Mechanics and its Applications. 508. 155–165. 55 indexed citations
16.
Ye, Renyu, Xinsheng Liu, Hai Zhang, & Jinde Cao. (2018). Global Mittag-Leffler Synchronization for Fractional-Order BAM Neural Networks with Impulses and Multiple Variable Delays via Delayed-Feedback Control Strategy. Neural Processing Letters. 49(1). 1–18. 50 indexed citations
17.
Zhang, Hai, et al.. (2017). LMI-based approach to stability analysis for fractional-order neural networks with discrete and distributed delays. International Journal of Systems Science. 49(3). 537–545. 64 indexed citations
18.
Zhang, Hai, Renyu Ye, Jinde Cao, & Ahmed Alsaedi. (2017). Delay-Independent Stability of Riemann–Liouville Fractional Neutral-Type Delayed Neural Networks. Neural Processing Letters. 53 indexed citations
19.
Zhang, Hai, et al.. (2017). Lyapunov Functional Approach to Stability Analysis of Riemann‐Liouville Fractional Neural Networks with Time‐Varying Delays. Asian Journal of Control. 20(5). 1938–1951. 48 indexed citations
20.
Zhang, Hai, Renyu Ye, Jinde Cao, & Ahmed Alsaedi. (2017). Existence and Globally Asymptotic Stability of Equilibrium Solution for Fractional-Order Hybrid BAM Neural Networks with Distributed Delays and Impulses. Complexity. 2017. 1–13. 17 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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