Mi Lv
Impact in
- Statistical and Nonlinear Physics top 0.5%
- stochastic dynamics and bifurcation
- Chaos control and synchronization
- Cognitive Neuroscience top 2%
- Neural dynamics and brain function
Papers in
-
- Neural dynamics and brain function 9
-
- stochastic dynamics and bifurcation 8
- Co-authors
- Jun Ma (8 shared papers)Chunni Wang (4 shared papers)Xinlin Song (1 shared paper)Guodong Ren (1 shared paper)Ying Xu (2 shared papers)Tasawar Hayat (1 shared paper)Ping Zhou (1 shared paper)Yuangen Yao (1 shared paper)
- Journals
- Chaos An Interdisciplinary Journal of Nonlinear Science (2 papers)Neurocomputing (2 papers)Nonlinear Dynamics (2 papers)Applied Mathematics and Computation (1 paper)IEEE/CAA Journal of Automatica Sinica (1 paper)
- Partner nations
- ChinaSaudi ArabiaPakistan
In The Last Decade
Mi Lv
12 papers receiving 1.2k citations
Mi Lv's Hit Papers
Peers
Comparison fields: 5 of 52
- Statistical and Nonlinear Physics 1.0k
- Cognitive Neuroscience 894
- Computer Networks and Communications 577
- Cellular and Molecular Neuroscience 193
- Electrical and Electronic Engineering 361
Countries citing papers authored by Mi Lv
This map shows the geographic impact of Mi Lv'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 Mi Lv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mi Lv more than expected).
Fields of papers citing papers by Mi Lv
This network shows the impact of papers produced by Mi Lv. 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 Mi Lv. The network helps show where Mi Lv may publish in the future.
Co-authors
The 23 scholars most cited alongside Mi Lv, 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 | Model of electrical activity in a neuron under magnetic flow effect Hit paper breakdown → | 2016 | 447 |
| 2 | 2016 | 282 | |
| 3 | 2017 | 175 | |
| 4 | 2018 | 100 | |
| 5 | 2024 | 58 | |
| 6 | 2017 | 47 | |
| 7 | 2023 | 27 | |
| 8 | 2016 | 24 | |
| 9 | 2024 | 21 | |
| 10 | 2019 | 18 | |
| 11 | 2024 | 11 | |
| 12 | 2023 | 3 |
About Mi Lv
Mi Lv is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics, Computer Networks and Communications, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering, having authored 12 papers that have together received 1.2k indexed citations. Recurring topics across this work include Neural dynamics and brain function (9 papers), stochastic dynamics and bifurcation (8 papers), Photoreceptor and optogenetics research (4 papers), Nonlinear Dynamics and Pattern Formation (3 papers), Smart Grid Security and Resilience (2 papers), Network Security and Intrusion Detection (2 papers), Advanced Memory and Neural Computing (2 papers) and Chaos-based Image/Signal Encryption (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (1.0k citations), Cognitive Neuroscience (894 citations), Computer Networks and Communications (577 citations), Cellular and Molecular Neuroscience (193 citations) and Electrical and Electronic Engineering (361 citations). Mi Lv has collaborated with scholars based in China, Saudi Arabia and Pakistan. Frequent co-authors include Jun Ma, Chunni Wang, Xinlin Song, Guodong Ren, Ying Xu, Tasawar Hayat, Ping Zhou, Yuangen Yao, Faris Alzahrani and Xikui Hu. Their work appears in journals such as Chaos An Interdisciplinary Journal of Nonlinear Science, Neurocomputing, Nonlinear Dynamics, Applied Mathematics and Computation and IEEE/CAA Journal of Automatica Sinica.
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.