Jun Mou
Impact in
- Statistical and Nonlinear Physics top 0.1%
- Chaos control and synchronization
- stochastic dynamics and bifurcation
-
- Chaos-based Image/Signal Encryption
- Advanced Steganography and Watermarking Techniques
Papers in
-
- Chaos control and synchronization 53
- stochastic dynamics and bifurcation 47
-
- Chaos-based Image/Signal Encryption 69
- Advanced Steganography and Watermarking Techniques 37
- Co-authors
- Yinghong CaoSanto BanerjeeFeifei YangHuizhen YanChenguang MaYushu ZhangLi XiongTianming Liu
- Journals
- Chaos Solitons & Fractals (18 papers)Nonlinear Dynamics (14 papers)IEEE Internet of Things Journal (9 papers)International Journal of Bifurcation and Chaos (9 papers)IEEE Access (8 papers)
- Partner nations
- ChinaItalySaudi Arabia
In The Last Decade
Jun Mou
154 papers receiving 4.6k citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Statistical and Nonlinear Physics 2.5k
- Computer Vision and Pattern Recognition 2.5k
- Computer Networks and Communications 952
- Cognitive Neuroscience 670
- Modeling and Simulation 153
Countries citing papers authored by Jun Mou
This map shows the geographic impact of Jun Mou'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 Jun Mou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Mou more than expected).
Fields of papers citing papers by Jun Mou
This network shows the impact of papers produced by Jun Mou. 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 Jun Mou. The network helps show where Jun Mou may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Mou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Encrypt a Story: A Video Segment Encryption Method Based on the Discrete Sinusoidal Memristive Rulkov Neuron Hit paper breakdown → | 2025 | 19 |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | A discrete Chialvo–Rulkov neuron network coupled with a novel memristor model: Design, Dynamical analysis, DSP implementation and its application Hit paper breakdown → | 2024 | 68 |
| 5 | 2024 | 6 | |
| 6 | 2024 | 43 | |
| 7 | 2024 | 9 | |
| 8 | 2024 | 15 | |
| 9 | 2024 | 19 | |
| 10 | 2024 | 19 | |
| 11 | 2024 | 14 | |
| 12 | 2024 | 16 | |
| 13 | 2023 | 40 | |
| 14 | 2023 | 1 | |
| 15 | 2023 | 0 | |
| 16 | 2023 | 33 | |
| 17 | 2023 | 25 | |
| 18 | 2023 | 26 | |
| 19 | 2022 | 0 | |
| 20 | 2019 | 43 |
About Jun Mou
Jun Mou is a scholar working on Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Modeling and Simulation, Cognitive Neuroscience and Computer Networks and Communications, having authored 169 papers that have together received 4.8k indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (69 papers), Advanced Memory and Neural Computing (58 papers), Chaos control and synchronization (53 papers), stochastic dynamics and bifurcation (47 papers), Advanced Steganography and Watermarking Techniques (37 papers), Neural dynamics and brain function (30 papers), Neural Networks Stability and Synchronization (27 papers) and Neural Networks and Applications (15 papers). The work is most often cited by research in Statistical and Nonlinear Physics (2.5k citations), Computer Vision and Pattern Recognition (2.5k citations), Computer Networks and Communications (952 citations), Cognitive Neuroscience (670 citations) and Modeling and Simulation (153 citations). Jun Mou has collaborated with scholars based in China, Italy and Saudi Arabia. Frequent co-authors include Yinghong Cao, Santo Banerjee, Feifei Yang, Huizhen Yan, Chenguang Ma, Yushu Zhang, Li Xiong, Tianming Liu, Hadi Jahanshahi and Xinyu Gao. Their work appears in journals such as Chaos Solitons & Fractals, Nonlinear Dynamics, IEEE Internet of Things Journal, International Journal of Bifurcation and Chaos and IEEE Access.
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.