B. Igelnik

1.4k citations
23 papers · 1.2k · 1 hit paper · h-index 10

Impact in

Papers in

B. Igelnik

23 papers receiving 1.1k citations

B. Igelnik's Hit Papers

Stochastic choice of basis functions in adaptive function approximation and the functional-link net 1995 · 792 citations
7920+10+20Years since publication250500750

Peers

B. Igelnik
Comparison fields: 5 of 72
  • Artificial Intelligence 593
  • Control and Systems Engineering 183
  • Computational Theory and Mathematics 96
  • Statistical and Nonlinear Physics 36
  • Computational Mathematics 2
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Dirk Schlierkamp-Voosen Germany
Lidong Wang China
Zhiming Zhang China
Zhongyu Chen China
Dirk V. Arnold Canada
Ahmed Ali Abdalla Esmin Brazil
Jianpei Zhang China
Henning Tolle Germany
R. Laur Germany
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Citations per field
00.5×5×11.8×
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Citations per year

Countries citing papers authored by B. Igelnik

Since Specialization
Citations

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

Fields of papers citing papers by B. Igelnik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside B. Igelnik, 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 B. Igelnik Line = papers co-authored together B. Igelnik links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Stochastic choice of basis functions in adaptive function approximation and the functional-link net
Hit paper breakdown →
1995792
2 200169
3 200360
4 199759
5 199954
6 199126
7 200119
8 200018
9 199513
10 199610
11 201110
12 20056
13 20095
14 19984
15 19984
16 19984
17 20013
18 20043
19 20022
20 19951

About B. Igelnik

B. Igelnik is a scholar working on Artificial Intelligence, Signal Processing, Management Information Systems, Materials Chemistry and Computational Theory and Mathematics, having authored 23 papers that have together received 1.2k indexed citations. Recurring topics across this work include Neural Networks and Applications (12 papers), Machine Learning in Materials Science (4 papers), Advanced Queuing Theory Analysis (2 papers), Advanced Clustering Algorithms Research (2 papers), Time Series Analysis and Forecasting (2 papers), Machine Learning and ELM (2 papers), Data Visualization and Analytics (2 papers) and Optical Polarization and Ellipsometry (2 papers). The work is most often cited by research in Artificial Intelligence (593 citations), Control and Systems Engineering (183 citations), Computational Theory and Mathematics (96 citations), Statistical and Nonlinear Physics (36 citations) and Computational Mathematics (2 citations). B. Igelnik has collaborated with scholars based in United States, Israel and Japan. Frequent co-authors include Yoh‐Han Pao, Steven R. LeClair, Y.-H. Pao, Jinyan Li, Yaakov Kogan, E. G. Coffman, M. Berndt, Allen G. Jackson, Shuichi Iwata and Klaus Brandenburg. Their work appears in journals such as Engineering Applications of Artificial Intelligence, Journal of Alloys and Compounds, Applied Mathematics and Computation, IEEE Transactions on Information Theory and Queueing Systems.

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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