U. Appel

415 citations
20 papers · 265 indexed · h-index 5

Impact in

Papers in

U. Appel

15 papers receiving 241 citations

Peers

U. Appel
Comparison fields: 5 of 68
  • Signal Processing 89
  • Cognitive Neuroscience 73
  • Statistics, Probability and Uncertainty 19
  • Control and Systems Engineering 54
  • Cardiology and Cardiovascular Medicine 46
Replace N. Suzumura with:
N. Suzumura Japan
Nicoletta Saulig Croatia
P. Lemmerling Belgium
Jorge Igual Spain
Ivo Bukovský Czechia
Y.N. Rao United States
Koby Todros Israel
A.C. Lindgren United States
M. Jaïdane-Saïdane Tunisia
Christian Gargour Canada
U. Appel relative to N. Suzumura Japan N. Suzumura's profile →
Citations per field
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N. Suzumura · 1×
Citations per year

Countries citing papers authored by U. Appel

Since Specialization
Citations

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

Fields of papers citing papers by U. Appel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 5 scholars most cited alongside U. Appel, 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 U. Appel Line = papers co-authored together U. Appel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 1983134
2 200060
3 198420
4 200319
5 199612
6 19754
7 20053
8 20022
9 19822
10 20022
11 20022
12 20052
13 19881
14 20051
15 19901
16
Multistage implementation of optimal reconstruction in noisy filter banks
19980
17 19870
18 19930
19 20050
20 20050

About U. Appel

U. Appel is a scholar working on Control and Systems Engineering, Cognitive Neuroscience, Signal Processing, Computational Mechanics and Biomedical Engineering, having authored 20 papers that have together received 265 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (7 papers), Advanced Adaptive Filtering Techniques (5 papers), Fault Detection and Control Systems (4 papers), Neural dynamics and brain function (4 papers), Advanced Statistical Process Monitoring (3 papers), Control Systems and Identification (3 papers), Structural Health Monitoring Techniques (3 papers) and Blind Source Separation Techniques (3 papers). The work is most often cited by research in Signal Processing (89 citations), Cognitive Neuroscience (73 citations), Statistics, Probability and Uncertainty (19 citations), Control and Systems Engineering (54 citations) and Cardiology and Cardiovascular Medicine (46 citations). U. Appel has collaborated with scholars based in Germany and Romania. Frequent co-authors include W. Wolf, R. Schnell, G. Staude, Reinhard Dengler and Anders Brandt. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, Information Sciences, Signal Processing, Biomedizinische Technik/Biomedical Engineering and IEEE Transactions on Circuits and 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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