Leonid Perlovsky

5.3k citations
204 papers · 2.9k · h-index 31

Impact in

    • Cognitive Science and Education Research
    • Neuroscience and Music Perception
    • Aesthetic Perception and Analysis
    • Neural dynamics and brain function
    • Neural Networks and Applications
    • Cognitive Science and Mapping

Papers in

    • Cognitive Science and Education Research 139
    • Neural Networks and Applications 63
    • Cognitive Science and Mapping 14
    • Target Tracking and Data Fusion in Sensor Networks 11
    • Cognitive Computing and Networks 7

Leonid Perlovsky

191 papers receiving 2.7k citations

Peers

Leonid Perlovsky
Comparison fields: 5 of 146
  • Cognitive Neuroscience 2.2k
  • Artificial Intelligence 1.1k
  • Computational Theory and Mathematics 363
  • Music 64
  • Experimental and Cognitive Psychology 249
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Citations per field
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Citations per year

Countries citing papers authored by Leonid Perlovsky

Since Specialization
Citations

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

Fields of papers citing papers by Leonid Perlovsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 204 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006161
2 1991107
3 199891
4 200987
5 200982
6 200974
7 201661
8 201359
9 200956
10 199748
11 201048
12 200748
13 200847
14 201346
15 201245
16 200742
17 201242
18 201041
19 201041
20 200938

About Leonid Perlovsky

Leonid Perlovsky is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Computational Theory and Mathematics, Cultural Studies and Aerospace Engineering, having authored 204 papers that have together received 2.9k indexed citations. Recurring topics across this work include Cognitive Science and Education Research (139 papers), Neural Networks and Applications (63 papers), Chaos, Complexity, and Education (25 papers), Language and cultural evolution (15 papers), Cognitive Science and Mapping (14 papers), Target Tracking and Data Fusion in Sensor Networks (11 papers), Fractal and DNA sequence analysis (9 papers) and Cognitive Computing and Networks (7 papers). The work is most often cited by research in Cognitive Neuroscience (2.2k citations), Artificial Intelligence (1.1k citations), Computational Theory and Mathematics (363 citations), Music (64 citations) and Experimental and Cognitive Psychology (249 citations). Leonid Perlovsky has collaborated with scholars based in United States, Brazil and Russia. Frequent co-authors include José F. Fontanari, Roman Ilin, Félix Schoeller, Nobuo Masataka, Ross Deming, Daniel S. Levine, Marie‐Claude Bonniot‐Cabanac, Michel Cabanac, Róbert Kozma and M. Cabanac. Their work appears in journals such as Physics of Life Reviews, Neural Networks, Frontiers in Psychology, Pattern Recognition Letters and Scientific Reports.

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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