Igor Belykh

2.9k citations
59 papers · 2.2k · h-index 23

Impact in

Papers in

Igor Belykh

56 papers receiving 2.1k citations

Peers

Igor Belykh
Comparison fields: 5 of 74
  • Statistical and Nonlinear Physics 1.3k
  • Computer Networks and Communications 1.9k
  • Cognitive Neuroscience 365
  • Acoustics and Ultrasonics 8
  • Geometry and Topology 63
Replace В. Н. Белых with:
В. Н. Белых Russia
Serhiy Yanchuk Germany
R. Jaimes-Reátegui Mexico
Fatihcan M. Atay Germany
R. Sevilla-Escoboza Mexico
Zhijun Li China
Toru Ohira Japan
Hilaire Bertrand Fotsin Cameroon
P. Perlikowski Poland
Т. Е. Вадивасова Russia
Igor Belykh relative to В. Н. Белых Russia В. Н. Белых's profile →
Citations per field
00.5×1.5×
В. Н. Белых · 1×
Citations per year

Countries citing papers authored by Igor Belykh

Since Specialization
Citations

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

Fields of papers citing papers by Igor Belykh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004398
2 2004290
3 2001155
4 2005126
5 2000121
6 200399
7 200689
8 200687
9 201168
10 200067
11 201362
12 201558
13 201353
14 201353
15 200342
16 201738
17 201637
18 201932
19 202130
20 202126

About Igor Belykh

Igor Belykh is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics, Molecular Biology, Cognitive Neuroscience and Biomedical Engineering, having authored 59 papers that have together received 2.2k indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (46 papers), Neural Networks Stability and Synchronization (19 papers), stochastic dynamics and bifurcation (16 papers), Chaos control and synchronization (14 papers), Gene Regulatory Network Analysis (10 papers), Neural dynamics and brain function (9 papers), Slime Mold and Myxomycetes Research (7 papers) and Structural Engineering and Vibration Analysis (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.3k citations), Computer Networks and Communications (1.9k citations), Cognitive Neuroscience (365 citations), Acoustics and Ultrasonics (8 citations) and Geometry and Topology (63 citations). Igor Belykh has collaborated with scholars based in United States, Russia and Switzerland. Frequent co-authors include В. Н. Белых, Martin Hasler, Russell Jeter, Erik Mosekilde, Maurizio Porfiri, M. Hasler, Henk Nijmeijer, Morten Colding‐Jørgensen, Mario di Bernardo and Jürgen Kurths. Their work appears in journals such as Chaos An Interdisciplinary Journal of Nonlinear Science, SIAM Journal on Applied Dynamical Systems, Physica D Nonlinear Phenomena, International Journal of Bifurcation and Chaos and Physical review. E.

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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