Ming‐Chung Ho

865 citations
33 papers · 691 indexed · h-index 11

Impact in

Papers in

Ming‐Chung Ho

31 papers receiving 644 citations

Peers

Ming‐Chung Ho
Comparison fields: 5 of 64
  • Statistical and Nonlinear Physics 553
  • Computer Networks and Communications 512
  • Cognitive Neuroscience 84
  • Computer Vision and Pattern Recognition 58
  • Mathematical Physics 10
Replace Yao-Chen Hung with:
Yao-Chen Hung Taiwan
Atiyeh Bayani Iran
Juan A. Sigüenza Spain
Luis F. Lago-Fernández Spain
Atefeh Ahmadi Iran
Ling Lü China
E. M. Shahverdiev United Kingdom
Ivan Bonamassa Israel
Juan Hugo García-López Mexico
Debabrata Biswas India
Ming‐Chung Ho relative to Yao-Chen Hung Taiwan Yao-Chen Hung's profile →
Citations per field
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Yao-Chen Hung · 1×
Citations per year

Countries citing papers authored by Ming‐Chung Ho

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Chung Ho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming‐Chung Ho. 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 Ming‐Chung Ho. The network helps show where Ming‐Chung Ho may publish in the future.

Co-authorship network

The 19 scholars most cited alongside Ming‐Chung Ho, 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 Ming‐Chung Ho Line = papers co-authored together Ming‐Chung Ho links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20230
2 20236
3 20221
4 20212
5 20162
6 20162
7 20151
8 201412
9 20128
10 201125
11 20100
12 20093
13 200857
14 200627
15 200517
16 20038
17 2002227
18 2002156
19
Determinism Test, Noise Estimate and Hidden Frequency Recognition: the Singular Value Decomposition Approach
19991
20 19991

About Ming‐Chung Ho

Ming‐Chung Ho is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications, Cognitive Neuroscience, Artificial Intelligence and Computational Theory and Mathematics, having authored 33 papers that have together received 691 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (16 papers), Chaos control and synchronization (15 papers), Neural dynamics and brain function (7 papers), EEG and Brain-Computer Interfaces (7 papers), Functional Brain Connectivity Studies (5 papers), stochastic dynamics and bifurcation (4 papers), Complex Systems and Time Series Analysis (4 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (553 citations), Computer Networks and Communications (512 citations), Cognitive Neuroscience (84 citations), Computer Vision and Pattern Recognition (58 citations) and Mathematical Physics (10 citations). Ming‐Chung Ho has collaborated with scholars based in Taiwan, China and Japan. Frequent co-authors include Yao-Chen Hung, I-Min Jiang, Zhiyu Liu, Yu‐Ting Huang, Chin‐Kun Hu, Chia‐Ju Liu, Tsung‐Ching Chen, Yu‐Te Lin, Ying‐Chao Hung and Jyh‐Long Chern. Their work appears in journals such as Physics Letters A, Chaos Solitons & Fractals, Optics Express, Europhysics Letters (EPL) and International Journal of Nonlinear Sciences and Numerical Simulation.

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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