G. Narayanan

1.0k citations
30 papers · 811 · h-index 15

Impact in

Papers in

G. Narayanan

29 papers receiving 801 citations

Peers

G. Narayanan
Comparison fields: 5 of 62
  • Computer Networks and Communications 588
  • Modeling and Simulation 106
  • Statistical and Nonlinear Physics 284
  • Artificial Intelligence 249
  • Control and Systems Engineering 179
Replace Ahmed Alsaedi with:
Ahmed Alsaedi Saudi Arabia
V. Vembarasan India
Pratap Anbalagan India
Qintao Gan China
Yingjie Fan China
Zhenkun Huang China
Zuowei Cai China
Farouk Chérif Tunisia
Lian Duan China
S. Mohamad Brunei
G. Narayanan relative to Ahmed Alsaedi Saudi Arabia Ahmed Alsaedi's profile →
Citations per field
00.5×
Ahmed Alsaedi · 1×
Citations per year

Countries citing papers authored by G. Narayanan

Since Specialization
Citations

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

Fields of papers citing papers by G. Narayanan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. Narayanan. 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 G. Narayanan. The network helps show where G. Narayanan may publish in the future.

Co-authors

The 25 scholars most cited alongside G. Narayanan, 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 G. Narayanan Line = papers co-authored together G. Narayanan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019105
2 202095
3 201974
4 201964
5 202257
6 202155
7 201946
8 202141
9 202134
10 202231
11 202228
12 202426
13 202221
14 202221
15 202314
16 202213
17 202412
18 202212
19 202311
20 202311

About G. Narayanan

G. Narayanan is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics, Electrical and Electronic Engineering, Molecular Biology and Control and Systems Engineering, having authored 30 papers that have together received 811 indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (21 papers), stochastic dynamics and bifurcation (7 papers), Nonlinear Dynamics and Pattern Formation (6 papers), Gene Regulatory Network Analysis (6 papers), Distributed Control Multi-Agent Systems (5 papers), Neural Networks and Applications (5 papers), Mathematical and Theoretical Epidemiology and Ecology Models (4 papers) and Advanced Memory and Neural Computing (4 papers). The work is most often cited by research in Computer Networks and Communications (588 citations), Modeling and Simulation (106 citations), Statistical and Nonlinear Physics (284 citations), Artificial Intelligence (249 citations) and Control and Systems Engineering (179 citations). G. Narayanan has collaborated with scholars based in India, Saudi Arabia and Thailand. Frequent co-authors include M. Syed Ali, Vineet Shekher, Sabri Arik, Bandana Priya, Sumit Saroha, Bashir Ahmad, Hamed Alsulami, Grienggrai Rajchakit, Ganesh Kumar Thakur and Ahmed Alsaedi. Their work appears in journals such as Communications in Nonlinear Science and Numerical Simulation, IEEE Access, IEEE Transactions on Systems Man and Cybernetics Systems, Neural Processing Letters and Information Sciences.

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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