Jie Jin

4.1k total citations · 3 hit papers
147 papers, 3.0k citations indexed

About

Jie Jin is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Jie Jin has authored 147 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Electrical and Electronic Engineering, 39 papers in Artificial Intelligence and 35 papers in Control and Systems Engineering. Recurrent topics in Jie Jin's work include Neural Networks and Applications (31 papers), Radio Frequency Integrated Circuit Design (25 papers) and Analog and Mixed-Signal Circuit Design (24 papers). Jie Jin is often cited by papers focused on Neural Networks and Applications (31 papers), Radio Frequency Integrated Circuit Design (25 papers) and Analog and Mixed-Signal Circuit Design (24 papers). Jie Jin collaborates with scholars based in China, United States and Hong Kong. Jie Jin's co-authors include Chunhua Wang, Fei Yu, Lv Zhao, Jay C. Unkeless, Shuo Cai, Chi-Ying Tsui, Nancy C. Andrews, Chaoyang Chen, Terry A. Krulwich and Aijia Ouyang and has published in prestigious journals such as Cell, Blood and Biochemistry.

In The Last Decade

Jie Jin

136 papers receiving 2.9k citations

Hit Papers

Dynamics analysis, synchronization and FPGA implementatio... 2024 2026 2025 2024 2025 2025 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jie Jin China 30 806 710 579 563 505 147 3.0k
Xiaopeng Wei China 36 325 0.4× 1.2k 1.7× 236 0.4× 420 0.7× 2.7k 5.4× 233 5.2k
Jin Zhang China 24 1.1k 1.3× 396 0.6× 118 0.2× 288 0.5× 443 0.9× 121 2.5k
Ho-Youl Jung South Korea 25 411 0.5× 273 0.4× 564 1.0× 255 0.5× 395 0.8× 105 2.2k
Xiao Wang China 33 262 0.3× 960 1.4× 55 0.1× 262 0.5× 1.7k 3.4× 183 3.5k
Bijoy K. Ghosh United States 35 531 0.7× 493 0.7× 1.4k 2.4× 191 0.3× 681 1.3× 212 4.0k
Xiaohui Liu China 32 176 0.2× 483 0.7× 525 0.9× 70 0.1× 361 0.7× 111 3.5k
Jin Yuan China 29 1.2k 1.5× 1.2k 1.7× 142 0.2× 62 0.1× 200 0.4× 229 3.4k
Dan Zhang China 36 687 0.9× 604 0.9× 2.6k 4.5× 335 0.6× 139 0.3× 250 4.3k
S.P. Bhattacharyya United States 39 617 0.8× 354 0.5× 4.9k 8.4× 396 0.7× 241 0.5× 269 6.6k
Jianshu Chen United States 24 369 0.5× 1.1k 1.5× 180 0.3× 106 0.2× 240 0.5× 149 2.8k

Countries citing papers authored by Jie Jin

Since Specialization
Citations

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

Fields of papers citing papers by Jie Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jie Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Jie Jin. A scholar is included among the top collaborators of Jie Jin 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 Jie Jin. Jie Jin 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.
Jin, Jie, et al.. (2025). An attractor-controllable memristive Hopfield neural network and its application on voice encryption. Integration. 105. 102500–102500. 5 indexed citations
2.
He, S., Fei Yu, R. P. Guo, et al.. (2025). Dynamic Analysis and FPGA Implementation of a Fractional-Order Memristive Hopfield Neural Network with Hidden Chaotic Dual-Wing Attractors. Fractal and Fractional. 9(9). 561–561. 10 indexed citations
3.
Yu, Fei, R. P. Guo, Fengyuan Zhang, et al.. (2025). Burst-firing and extreme multistability in a dual-neuron fractional-order memristive HNN with hardware implementation. Chaos An Interdisciplinary Journal of Nonlinear Science. 35(11).
4.
Jin, Jie, et al.. (2025). A Novel Dynamic Hill Cipher and Its Applications on Medical IoT. IEEE Internet of Things Journal. 12(10). 14297–14308. 29 indexed citations breakdown →
5.
Jin, Jie, et al.. (2025). A fixed-time convergence robust zeroing neural network for the synchronization of memristor-based chaotic systems. Communications in Nonlinear Science and Numerical Simulation. 152. 109479–109479. 1 indexed citations
6.
Jin, Jie, et al.. (2025). A review of Zeroing neural network: Theory, algorithm and application. Neurocomputing. 643. 130425–130425. 6 indexed citations
7.
Zhao, Lv, Xin Liu, & Jie Jin. (2024). A novel fuzzy-type zeroing neural network for dynamic matrix solving and its applications. Journal of the Franklin Institute. 361(15). 107143–107143. 5 indexed citations
9.
Liu, Xin, et al.. (2024). A noise‐tolerant fuzzy‐type zeroing neural network for robust synchronization of chaotic systems. Concurrency and Computation Practice and Experience. 36(22). 16 indexed citations
10.
Jin, Jie, Lan Zhou, Chaoyang Chen, et al.. (2024). A Complex-Valued Variant-Parameter Robust Zeroing Neural Network Model and its Applications. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(2). 1303–1321. 25 indexed citations
11.
Jin, Jie, et al.. (2024). A fuzzy activation function based zeroing neural network for dynamic Arnold map image cryptography. Mathematics and Computers in Simulation. 230. 456–469. 5 indexed citations
12.
Yu, Fei, Xinxin Kong, Wei Yao, et al.. (2024). Dynamics analysis, synchronization and FPGA implementation of multiscroll Hopfield neural networks with non-polynomial memristor. Chaos Solitons & Fractals. 179. 114440–114440. 119 indexed citations breakdown →
13.
Jin, Jie, et al.. (2024). A New-Type Zeroing Neural Network Model and Its Application in Dynamic Cryptography. IEEE Transactions on Emerging Topics in Computational Intelligence. 9(1). 176–191. 34 indexed citations
14.
Jin, Jie, et al.. (2023). A noise tolerant parameter-variable zeroing neural network and its applications. Mathematics and Computers in Simulation. 207. 482–498. 15 indexed citations
15.
Yu, Fei, et al.. (2020). Analysis of a New Hidden Attractor Coupled Chaotic System and Application of Its Weak Signal Detection. Mathematical Problems in Engineering. 2020. 1–15. 6 indexed citations
16.
Fan, YouZhe, et al.. (2018). Efficient Partial-Sum Network Architectures for List Successive-Cancellation Decoding of Polar Codes. IEEE Transactions on Signal Processing. 66(14). 3848–3858. 8 indexed citations
17.
Jin, Jie, Lin Xiao, Xi Yang, Bolin Liao, & Shu Li. (2016). Dual-mode multi-phase sinusoidal oscillator with equal amplitudes. Engineering review. 36(3). 211–220. 3 indexed citations
18.
Jin, Jie. (2016). Novel quadrature voltage controlled oscillator using series transistors coupling. Indian Journal of Pure & Applied Physics. 54(12). 765–770. 1 indexed citations
19.
Jin, Jie, Chunhua Wang, & Jingru Sun. (2015). Novel Third-Order Quadrature Oscillators with Grounded Capacitors. 56(2). 207–216. 5 indexed citations
20.
Jin, Jie, et al.. (2014). Novel digitally programmable multiphase voltage controlled oscillator and its stability discussion. Microelectronics Reliability. 54(3). 595–600. 6 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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