Mi Lv

1.4k citations
12 papers · 1.3k · 2 hit papers · h-index 11

Impact in

Papers in

Mi Lv

12 papers receiving 1.2k citations

Mi Lv's Hit Papers

Multiple modes of electrical activities in a new neuron model under electromagnetic radiation 2016 · 291 citations
2910+3+6Years since publication100200300400

Peers

Mi Lv
Comparison fields: 5 of 42
  • Statistical and Nonlinear Physics 779
  • Computer Networks and Communications 526
  • Cognitive Neuroscience 445
  • Electrical and Electronic Engineering 282
  • Geometry and Topology 42
Replace Xinlin Song with:
Xinlin Song China
Guodong Ren China
Mengyan Ge China
Ping Zhou China
Xuan Zhan China
Zhuoqin Yang China
O. De Feo Switzerland
Bin Deng China
Shenquan Liu China
Zhao Yao China
Mi Lv relative to Xinlin Song China Xinlin Song's profile →
Citations per field
00.5×1.5×
Xinlin Song · 1×
Citations per year

Countries citing papers authored by Mi Lv

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Mi Lv Line = papers co-authored together Mi Lv links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1
Model of electrical activity in a neuron under magnetic flow effect
Hit paper breakdown →
2016462
2
Multiple modes of electrical activities in a new neuron model under electromagnetic radiation
Hit paper breakdown →
2016291
3 2017179
4 2018101
5 202463
6 201751
7 202329
8 201625
9 202425
10 201918
11 202413
12 20235

About Mi Lv

Mi Lv is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience, Computer Networks and Communications, Control and Systems Engineering and Electrical and Electronic Engineering, having authored 12 papers that have together received 1.3k indexed citations. Recurring topics across this work include stochastic dynamics and bifurcation (5 papers), Neural dynamics and brain function (5 papers), Nonlinear Dynamics and Pattern Formation (4 papers), Advanced Memory and Neural Computing (2 papers), Smart Grid Security and Resilience (2 papers), Adaptive Control of Nonlinear Systems (1 paper), Traffic control and management (1 paper) and Chaos control and synchronization (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (779 citations), Computer Networks and Communications (526 citations), Cognitive Neuroscience (445 citations), Electrical and Electronic Engineering (282 citations) and Geometry and Topology (42 citations). Mi Lv has collaborated with scholars based in China, Saudi Arabia and Pakistan. Frequent co-authors include Jun Ma, Chunni Wang, Guodong Ren, Xinlin Song, Ying Xu, Ping Zhou, Tasawar Hayat, Faris Saeed Alzahrani, Yuangen Yao and Xikui Hu. Their work appears in journals such as Nonlinear Dynamics, Neurocomputing, Chaos An Interdisciplinary Journal of Nonlinear Science, Science China Technological Sciences and ACS Applied Materials & Interfaces.

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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