Bogdan M. Wilamowski

7.4k citations
183 papers · 4.6k indexed · 3 hit papers · h-index 33

Bogdan M. Wilamowski

175 papers receiving 4.3k citations

Hit Papers

Selection of Proper Neural Network Sizes and Architecture...3052010202620152020100200300400

Peers

Bogdan M. Wilamowski
Comparison fields: 5 of 170
  • Control and Systems Engineering 1.3k
  • Artificial Intelligence 1.7k
  • Electrical and Electronic Engineering 1.4k
  • Computer Vision and Pattern Recognition 464
  • Signal Processing 197
Replace Danil Prokhorov with:
Danil Prokhorov United States
Mohammad Teshnehlab Iran
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Countries citing papers authored by Bogdan M. Wilamowski

Since Specialization
Citations

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

Fields of papers citing papers by Bogdan M. Wilamowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bogdan M. Wilamowski. 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 Bogdan M. Wilamowski. The network helps show where Bogdan M. Wilamowski may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 201787
2 20162
3 20153
4 201310
5
Efficient neural network architectures and Advanced training algorithms
20104
6 2010121
7
Improved Computation for Levenberg–Marquardt Trainingbreakdown →
2010465
8 20102
9 2008114
10 20088
11
Major challenges of IEEE Transactions on Industrial Electronics [My View]
2007106
12 20075
13 20063
14 200621
15 20031
16 200366
17 20021
18 200211
19
Low power, current mode CMOS circuits for synthesis of arbitrary nonlinear functions
200011
20 199939

About Bogdan M. Wilamowski

Bogdan M. Wilamowski is a scholar working on Artificial Intelligence, Control and Systems Engineering and Signal Processing, having authored 183 papers that have together received 4.6k indexed citations. Recurring topics across this work include Neural Networks and Applications (90 papers), Fuzzy Logic and Control Systems (39 papers), Analog and Mixed-Signal Circuit Design (23 papers), Sensor Technology and Measurement Systems (20 papers), Fault Detection and Control Systems (17 papers), Machine Learning and ELM (15 papers), Advancements in Semiconductor Devices and Circuit Design (14 papers) and Experimental Learning in Engineering (9 papers). The work is most often cited by research in Control and Systems Engineering (1.3k citations), Artificial Intelligence (1.7k citations) and Electrical and Electronic Engineering (1.4k citations). Bogdan M. Wilamowski has collaborated with scholars based in United States, Poland and Türkiye. Frequent co-authors include Hao Yu, Hao Yu, Tiantian Xie, Okyay Kaynak, Janusz Kolbusz, Paweł Różycki, S. Paszczynski, David W. Hunter, Bo Wu and Michael S. Pukish. Their work appears in journals such as IEEE Transactions on Industrial Electronics, IEEE Transactions on Electron Devices and IEEE Transactions on Cybernetics.

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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