Ivan Dvořák

615 citations
9 papers · 383 indexed · h-index 6

Impact in

Papers in

Ivan Dvořák

9 papers receiving 359 citations

Peers

Ivan Dvořák
Comparison fields: 5 of 69
  • Statistical and Nonlinear Physics 176
  • Cognitive Neuroscience 199
  • Economics and Econometrics 124
  • Signal Processing 45
  • Computer Networks and Communications 58
Replace Wolfgang Liebert with:
Wolfgang Liebert Germany
M.A. Jiménez-Montaño Mexico
I. D. Zimmerman United States
L. Romanelli Argentina
Yonghong Chen China
A. Passamante United States
David E. Lerner United States
Dejin Yu United Kingdom
S.H. Isabelle United States
Daniel T. Kaplan Canada
Ivan Dvořák relative to Wolfgang Liebert Germany Wolfgang Liebert's profile →
Citations per field
00.5×4.7×
Wolfgang Liebert · 1×
Citations per year

Countries citing papers authored by Ivan Dvořák

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Dvořák

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 7 scholars most cited alongside Ivan Dvořák, 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 Ivan Dvořák Line = papers co-authored together Ivan Dvořák links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
Rizikový a rozvojový kapitál : Venture capital.
19981
2 199359
3 199372
4 199280
5
Mathematical Approaches to Brain Functioning Diagnostics
199174
6 199036
7 198658
8 19852
9 19821

About Ivan Dvořák

Ivan Dvořák is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications, Cognitive Neuroscience, Condensed Matter Physics and Economics and Econometrics, having authored 9 papers that have together received 383 indexed citations. Recurring topics across this work include Chaos control and synchronization (4 papers), Nonlinear Dynamics and Pattern Formation (3 papers), Neural dynamics and brain function (2 papers), Complex Systems and Time Series Analysis (2 papers), Functional Brain Connectivity Studies (1 paper), Protein Structure and Dynamics (1 paper), Cardiomyopathy and Myosin Studies (1 paper) and Quantum chaos and dynamical systems (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (176 citations), Cognitive Neuroscience (199 citations), Economics and Econometrics (124 citations), Signal Processing (45 citations) and Computer Networks and Communications (58 citations). Ivan Dvořák has collaborated with scholars based in Czechia, Switzerland and United States. Frequent co-authors include Milan Paluš, Arun V. Holden, Jan Klaschka, Dietrich Lehmann, Christoph M. Michel, Jiřı́ Wackermann and Petr Kůrka. Their work appears in journals such as Physics Letters A, Physica D Nonlinear Phenomena, Electroencephalography and Clinical Neurophysiology, Mathematical Biosciences and Medical Entomology and Zoology.

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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