T. Kozek

25 papers receiving 523 citations

Peers

T. Kozek
Comparison fields: 5 of 57
  • Computer Networks and Communications 393
  • Artificial Intelligence 325
  • Computational Theory and Mathematics 133
  • Statistical and Nonlinear Physics 82
  • Electrical and Electronic Engineering 187
Replace Csaba Rekeczky with:
Csaba Rekeczky Hungary
Gabriele Manganaro United States
Xue-Bin Liang United States
H. Harrer Germany
P. Szolgay Hungary
D.E. Van den Bout United States
A. Lozowski United States
Xiaoqiang Wang China
Duqu Wei China
Recai Kılıç Türkiye
T. Kozek relative to Csaba Rekeczky Hungary Csaba Rekeczky's profile →
Citations per field
00.5×1.5×2.4×
Csaba Rekeczky · 1×
Citations per year

Countries citing papers authored by T. Kozek

Since Specialization
Citations

This map shows the geographic impact of T. Kozek'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 T. Kozek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Kozek more than expected).

Fields of papers citing papers by T. Kozek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside T. Kozek, 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 T. Kozek Line = papers co-authored together T. Kozek links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993145
2 1995140
3 199570
4 199226
5 199625
6
Solving partial differential equations by CNN
199319
7
Smart image scanning algorithms for the CNN universal machine
199517
8 199916
9 200016
10 200214
11 199913
12 199612
13 199911
14 200211
15 20029
16 19974
17 20023
18 20023
19
Constructive use of spatiotemporal dynamics in cellular neural networks
19962
20
Genetic algorithm for CNN template learning. (Memo UCB/ERL No. M92/82.)
19921

About T. Kozek

T. Kozek is a scholar working on Computer Networks and Communications, Artificial Intelligence, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 25 papers that have together received 562 indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (19 papers), Neural Networks and Applications (18 papers), Advanced Memory and Neural Computing (13 papers), Neural dynamics and brain function (3 papers), Cellular Automata and Applications (2 papers), Nonlinear Dynamics and Pattern Formation (2 papers), Image and Signal Denoising Methods (2 papers) and Image Enhancement Techniques (1 paper). The work is most often cited by research in Computer Networks and Communications (393 citations), Artificial Intelligence (325 citations), Computational Theory and Mathematics (133 citations), Statistical and Nonlinear Physics (82 citations) and Electrical and Electronic Engineering (187 citations). T. Kozek has collaborated with scholars based in Hungary, United States and Germany. Frequent co-authors include T. Roska, Leon O. Chua, Dietrich E. Wolf, Ronald Tetzlaff, Frank Puffer, Ákos Zarándy, Tamás Roska, D.L. Vilariño, Tamás Szirányi and P. Szolgay. Their work appears in journals such as International Journal of Circuit Theory and Applications, IEEE Transactions on Multimedia, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Circuits and Devices Magazine and Lecture notes in computer science.

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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