Daniel Graupe
Impact in
- Cognitive Neuroscience top 2%
- EEG and Brain-Computer Interfaces
- Signal Processing top 2%
- Blind Source Separation Techniques
Papers in
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- Muscle activation and electromyography studies 35
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- EEG and Brain-Computer Interfaces 30
- Co-authors
- Kate H. Kohn (12 shared papers)Vivek Nigam (1 shared paper)Hubert Kordylewski (11 shared papers)A.A. Beex (1 shared paper)Daniela Tuninetti (11 shared papers)Michael A. Wincek (1 shared paper)Konstantin V. Slavin (9 shared papers)Ishita Basu (9 shared papers)
- Journals
- IEEE Transactions on Automatic Control (11 papers)International Journal of Systems Science (11 papers)Neurological Research (11 papers)IEEE Transactions on Biomedical Engineering (2 papers)Technometrics (2 papers)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Daniel Graupe
121 papers receiving 3.6k citations
Peers
Comparison fields: 5 of 169
- Cognitive Neuroscience 1.2k
- Signal Processing 519
- Cellular and Molecular Neuroscience 746
- Biomedical Engineering 1.4k
- Computational Mathematics 18
Countries citing papers authored by Daniel Graupe
This map shows the geographic impact of Daniel Graupe'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 Daniel Graupe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Graupe more than expected).
Fields of papers citing papers by Daniel Graupe
This network shows the impact of papers produced by Daniel Graupe. 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 Daniel Graupe. The network helps show where Daniel Graupe may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Graupe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 130 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1997 | 354 | |
| 2 | 2004 | 306 | |
| 3 | 1975 | 298 | |
| 4 | 2013 | 297 | |
| 5 | 1982 | 178 | |
| 6 | 2007 | 176 | |
| 7 | 1978 | 174 | |
| 8 | 1978 | 138 | |
| 9 | Punctured Convolutional Codes of Rate (n - 1)/n and Simplified Maximum Likelihood Decoding | 1979 | 127 |
| 10 | 2001 | 91 | |
| 11 | 1998 | 91 | |
| 12 | 1985 | 85 | |
| 13 | 1989 | 84 | |
| 14 | 2013 | 80 | |
| 15 | 1987 | 76 | |
| 16 | 1975 | 75 | |
| 17 | 2007 | 67 | |
| 18 | 1995 | 63 | |
| 19 | 2009 | 52 | |
| 20 | 2010 | 52 |
About Daniel Graupe
Daniel Graupe is a scholar working on Biomedical Engineering, Cognitive Neuroscience, Artificial Intelligence, Signal Processing and Control and Systems Engineering, having authored 130 papers that have together received 3.9k indexed citations. Recurring topics across this work include Muscle activation and electromyography studies (35 papers), EEG and Brain-Computer Interfaces (30 papers), Neural Networks and Applications (22 papers), Neuroscience and Neural Engineering (20 papers), Blind Source Separation Techniques (17 papers), Control Systems and Identification (16 papers), Fault Detection and Control Systems (13 papers) and Advanced Adaptive Filtering Techniques (12 papers). The work is most often cited by research in Cognitive Neuroscience (1.2k citations), Signal Processing (519 citations), Cellular and Molecular Neuroscience (746 citations), Biomedical Engineering (1.4k citations) and Computational Mathematics (18 citations). Daniel Graupe has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Kate H. Kohn, Vivek Nigam, Hubert Kordylewski, A.A. Beex, Daniela Tuninetti, Michael A. Wincek, Konstantin V. Slavin, Ishita Basu, Jason H. Moore and Aaron S. Field. Their work appears in journals such as IEEE Transactions on Automatic Control, International Journal of Systems Science, Neurological Research, IEEE Transactions on Biomedical Engineering and Technometrics.
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.