Andrzej Majkowski

49 papers receiving 551 citations

Peers

Andrzej Majkowski
Comparison fields: 5 of 86
  • Experimental and Cognitive Psychology 220
  • Human-Computer Interaction 91
  • Cognitive Neuroscience 298
  • Signal Processing 101
  • Computer Vision and Pattern Recognition 117
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Marcin Kołodziej Poland
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Citations per year

Countries citing papers authored by Andrzej Majkowski

Since Specialization
Citations

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

Fields of papers citing papers by Andrzej Majkowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Andrzej Majkowski, 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 Andrzej Majkowski Line = papers co-authored together Andrzej Majkowski links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017181
2 202048
3 202035
4 201234
5 201724
6 201824
7 201922
8
Linear discriminant analysis as EEG features reduction technique for brain-computer interfaces
201216
9 201415
10 202214
11
A new method of feature extraction from EEG signal for braincomputer interface design
201012
12 201811
13 201210
14 201810
15
Matlab FE_Toolbox - an universal utility for feature extraction of EEG signals for BCI realization
20109
16 20179
17 20239
18 20198
19 20028
20 20157

About Andrzej Majkowski

Andrzej Majkowski is a scholar working on Cognitive Neuroscience, Signal Processing, Artificial Intelligence, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition, having authored 59 papers that have together received 607 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (34 papers), Neuroscience and Neural Engineering (11 papers), Neural Networks and Applications (11 papers), Emotion and Mood Recognition (9 papers), Blind Source Separation Techniques (8 papers), Neural dynamics and brain function (7 papers), Non-Invasive Vital Sign Monitoring (5 papers) and Gaze Tracking and Assistive Technology (4 papers). The work is most often cited by research in Experimental and Cognitive Psychology (220 citations), Human-Computer Interaction (91 citations), Cognitive Neuroscience (298 citations), Signal Processing (101 citations) and Computer Vision and Pattern Recognition (117 citations). Andrzej Majkowski has collaborated with scholars based in Poland. Frequent co-authors include Marcin Kołodziej, Remigiusz J. Rak, Paweł Tarnowski, Andrzej Rysz, Piotr Francuz, Dariusz Zapała, Agnieszka Pluta, Paweł Augustynowicz, S. Osowski and Andrzej Cichocki. Their work appears in journals such as Applied Sciences, Bulletin of the Polish Academy of Sciences Technical Sciences, Computational Intelligence and Neuroscience, Frontiers in Neuroscience and IEEE Sensors Journal.

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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