Dimiter Prodanov

1.3k citations
61 papers · 931 indexed · h-index 17

Impact in

Papers in

Dimiter Prodanov

55 papers receiving 901 citations

Peers

Dimiter Prodanov
Comparison fields: 5 of 127
  • Cellular and Molecular Neuroscience 387
  • Modeling and Simulation 76
  • Biophysics 80
  • Cognitive Neuroscience 145
  • Biomedical Engineering 278
Replace Marja‐Leena Linne with:
Marja‐Leena Linne Finland
Christopher P. Fall United States
Jan Hrabě United States
Fidel Santamarı́a United States
Daniel J. Tward United States
Alexander O. Tarakanov Russia
Mehmet N. Oguztöreli Canada
Jorge Riera United States
Jonathan R. Silva United States
Dušan Ristanović Serbia
Dimiter Prodanov relative to Marja‐Leena Linne Finland Marja‐Leena Linne's profile →
Citations per field
00.5×6.2×
Marja‐Leena Linne · 1×
Citations per year

Countries citing papers authored by Dimiter Prodanov

Since Specialization
Citations

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

Fields of papers citing papers by Dimiter Prodanov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20240
3 20215
4 201932
5 201910
6 201829
7 201764
8 2016116
9 201612
10 201377
11 201250
12 20126
13 20116
14 20100
15
Quantitative Microscopic Analysis of Myelinated Nerve Fibers
20102
16 201090
17 200916
18 20088
19 200519
20 200533

About Dimiter Prodanov

Dimiter Prodanov is a scholar working on Modeling and Simulation, Chemical Health and Safety, Biophysics, Numerical Analysis and Mathematical Physics, having authored 61 papers that have together received 931 indexed citations. Recurring topics across this work include Fractional Differential Equations Solutions (15 papers), Neuroscience and Neural Engineering (9 papers), Cell Image Analysis Techniques (8 papers), Iterative Methods for Nonlinear Equations (6 papers), Statistical Mechanics and Entropy (5 papers), EEG and Brain-Computer Interfaces (5 papers), Mathematical and Theoretical Analysis (4 papers) and Algebraic and Geometric Analysis (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (387 citations), Modeling and Simulation (76 citations), Biophysics (80 citations), Cognitive Neuroscience (145 citations) and Biomedical Engineering (278 citations). Dimiter Prodanov has collaborated with scholars based in Belgium, Bulgaria and Netherlands. Frequent co-authors include Jean Delbeke, Dries Braeken, Enrico Marani, Carmen Bartic, H.K.P. Feirabend, Volodymyr B. Bogdanov, Jean Schoenen, Sylvie Multon, Carlos G. Dotti and Olena V. Bogdanova. Their work appears in journals such as Frontiers in Neuroinformatics, Chaos Solitons & Fractals, Frontiers in Neuroscience, Fractional Calculus and Applied Analysis and IEEE Open Journal of Engineering in Medicine and Biology.

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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