Jianming Cai
- Statistical and Nonlinear Physics top 5%
- Electrical and Electronic Engineering
- Cognitive Neuroscience top 10%
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Topics
- stochastic dynamics and bifurcation (5 papers)Advanced Memory and Neural Computing (5 papers)Neural dynamics and brain function (4 papers)
- Cited by
- Statistical and Nonlinear PhysicsCognitive NeuroscienceComputer Networks and Communications
- Journals
- IEEE Transactions on Systems Man and Cybernetics SystemsNonlinear DynamicsIEEE Transactions on Circuits and Systems I Regular Papers
- Partner nations
- China
In The Last Decade
Jianming Cai
6 papers receiving 336 citations
Hit Papers
Peers
Comparison fields: 5 of 29
- Statistical and Nonlinear Physics 213
- Electrical and Electronic Engineering 182
- Cognitive Neuroscience 151
- Artificial Intelligence 107
- Computer Networks and Communications 87
Countries citing papers authored by Jianming Cai
This map shows the geographic impact of Jianming Cai'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 Jianming Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianming Cai more than expected).
Fields of papers citing papers by Jianming Cai
This network shows the impact of papers produced by Jianming Cai. 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 Jianming Cai. The network helps show where Jianming Cai may publish in the future.
Co-authorship network of co-authors of Jianming Cai
This figure shows the co-authorship network connecting the top 25 collaborators of Jianming Cai. A scholar is included among the top collaborators of Jianming Cai 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 Jianming Cai. Jianming Cai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 44 | |
| 2 | Memristor Synapse-Driven Simplified Hopfield Neural Network: Hidden Dynamics, Attractor Control, and Circuit Implementationbreakdown → | 76 |
| 3 | 66 | |
| 4 | 67 | |
| 5 | 51 | |
| 6 | 41 |
About Jianming Cai
Jianming Cai is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Electrical and Electronic Engineering, having authored 6 papers that have together received 345 indexed citations. Recurring topics across this work include stochastic dynamics and bifurcation (5 papers), Advanced Memory and Neural Computing (5 papers) and Neural dynamics and brain function (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (213 citations), Cognitive Neuroscience (151 citations) and Computer Networks and Communications (87 citations). Jianming Cai has collaborated with scholars based in China. Frequent co-authors include Han Bao, Bocheng Bao, Quan Xu, Chengjie Chen, Fuhong Min, Jingting Hu, Xi Zhang, Mo Chen, Zhongyun Hua and Yunzhen Zhang. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Systems, Nonlinear Dynamics and IEEE Transactions on Circuits and Systems I Regular Papers.
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.