Yongqing Yang

2.3k total citations
98 papers, 1.9k citations indexed

About

Yongqing Yang is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics and Electrical and Electronic Engineering. According to data from OpenAlex, Yongqing Yang has authored 98 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Computer Networks and Communications, 33 papers in Statistical and Nonlinear Physics and 23 papers in Electrical and Electronic Engineering. Recurrent topics in Yongqing Yang's work include Neural Networks Stability and Synchronization (72 papers), Distributed Control Multi-Agent Systems (35 papers) and Nonlinear Dynamics and Pattern Formation (33 papers). Yongqing Yang is often cited by papers focused on Neural Networks Stability and Synchronization (72 papers), Distributed Control Multi-Agent Systems (35 papers) and Nonlinear Dynamics and Pattern Formation (33 papers). Yongqing Yang collaborates with scholars based in China, Saudi Arabia and South Korea. Yongqing Yang's co-authors include Jinde Cao, Fei Wang, Lingzhong Zhang, Manfeng Hu, Zhenyuan Xu, Liuxiao Guo, Xin Sui, Li Li, Fei Wang and Xianyun Xu and has published in prestigious journals such as Journal of Biological Chemistry, Information Sciences and IEEE Transactions on Fuzzy Systems.

In The Last Decade

Yongqing Yang

91 papers receiving 1.9k citations

Peers

Yongqing Yang

CNC

SNP

EEE

CSE

Zunshui Cheng China

Chaouki Aouiti Tunisia

Qintao Gan China

Lihong Huang China

G. Velmurugan India

Chengdai Huang China

Wenxue Li China

R. Vadivel Thailand

Prakash Mani India

Anitha Karthikeyan Ethiopia

Zunshui Cheng China

Yongqing Yang

1.0k ×0.7

CNC

536 ×0.6

SNP

228 ×0.6

265 ×0.8

EEE

246 ×0.9

CSE

Citations per year, relative to Yongqing Yang Yongqing Yang (= 1×) peers Zunshui Cheng

Countries citing papers authored by Yongqing Yang

Since Specialization

Citations

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

Fields of papers citing papers by Yongqing Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yongqing Yang

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

All Works

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20 of 20 papers shown

Park, Ju H., et al.. (2024). Dynamic Weighted Average Consensus of Open Time-Varying Multi-Agent Systems on Time Scales via Sampled-Data Impulsive Communication. IEEE Transactions on Network Science and Engineering. 11(5). 4330–4343. 2 indexed citations

Sui, Xin, Yongqing Yang, & Fei Wang. (2024). Consensus of multi-agent systems with randomly occurring nonlinearities via uncertain pinning control under switching topologies. Neural Processing Letters. 56(2).

Weng, Hong, et al.. (2024). Finite-Time Projective Synchronization in Fractional-Order Inertial Memristive Neural Networks: A Novel Approach to Image Encryption. Fractal and Fractional. 8(11). 631–631. 3 indexed citations

Yang, Yongqing, et al.. (2023). Practical time-boundary consensus for fractional-order multi-agent systems under well-known and estimable topology. Applied Mathematics and Computation. 464. 128400–128400. 2 indexed citations

Wang, Fei, Chuan Zhang, Yongqing Yang, & Ning Li. (2023). Observer-based consensus of fractional order parabolic PDEs agents on directed networks via boundary communication. Chaos Solitons & Fractals. 170. 113332–113332. 11 indexed citations

Yang, Yongqing, et al.. (2023). Synchronization of fractional-order reaction–diffusion neural networks with Markov parameter jumping: Asynchronous boundary quantization control. Chaos Solitons & Fractals. 173. 113622–113622. 9 indexed citations

Yang, Yongqing, et al.. (2023). Finite-time bipartite lag synchronization of coupled memristive neural networks with uncertain disturbances via hybrid control. Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering. 237(8). 1454–1468. 1 indexed citations

Yang, Yongqing, et al.. (2022). Different Control Strategies for Fixed-Time Synchronization of Inertial Memristive Neural Networks. Neural Processing Letters. 54(5). 3657–3678. 5 indexed citations

Yang, Yongqing, et al.. (2021). Leaderless and leader-following consensus of heterogeneous second-order multi-agent systems on time scales: an asynchronous impulsive approach. International Journal of Control. 95(9). 2543–2553. 6 indexed citations

10.

Hu, Aihua, et al.. (2020). Pinning exponential boundedness of fractional-order multi-agent systems with intermittent combination event-triggered protocol. International Journal of Systems Science. 52(4). 874–888. 2 indexed citations

11.

Yang, Yongqing, et al.. (2019). Maximum likelihood gradient‐based iterative estimation for multivariable systems. IET Control Theory and Applications. 13(11). 1683–1691. 9 indexed citations

12.

Wang, Fei, Zhaowen Zheng, & Yongqing Yang. (2019). Synchronization of Complex Dynamical Networks with Hybrid Time Delay under Event‐Triggered Control: The Threshold Function Method. Complexity. 2019(1). 5 indexed citations

13.

Li, Liangliang, et al.. (2016). Proteomic analysis of differentially expressed proteins in the three developmental stages of Trichinella spiralis. Veterinary Parasitology. 231. 32–38. 27 indexed citations

14.

Zhang, Lingzhong, Yongqing Yang, & Fei Wang. (2016). Projective synchronization of fractional-order memristive neural networks with switching jumps mismatch. Physica A Statistical Mechanics and its Applications. 471. 402–415. 41 indexed citations

15.

Li, Li, et al.. (2014). The exponential stability of BAM neural networks with leakage time-varying delays and sampled-data state feedback input. Advances in Difference Equations. 2014(1). 3 indexed citations

16.

Yang, Yongqing. (2012). Dispatching model of continuous consumption resources in wartime under insufficient supply. Systems engineering and electronics. 1 indexed citations

17.

Hu, Mingxing, et al.. (2012). Passivity analysis for switched generalized neural networks with time-varying delay and uncertain output. IMA Journal of Mathematical Control and Information. 30(3). 407–422. 19 indexed citations

18.

Yang, Yongqing. (2011). Fuzzy programming model of emergency resources dispatching. Computer Engineering and Applications Journal. 1 indexed citations

19.

Xu, Zhenyuan, et al.. (2011). An example of realizing "order+order=chaos" via synchronization. Acta Physica Sinica. 60(1). 10515–10515. 2 indexed citations

20.

Hu, Manfeng, Yongqing Yang, Zhenyuan Xu, Rong Zhang, & Liuxiao Guo. (2007). Projective synchronization in drive-response dynamical networks. Physica A Statistical Mechanics and its Applications. 381. 457–466. 58 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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