Jürgen Prestin
- Applied Mathematics top 2%
- Mathematical Analysis and Transform Methods 24
- Mathematical functions and polynomials 18
- Numerical Analysis top 5%
- Mathematical Approximation and Integration 11
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- Image and Signal Denoising Methods 16
- Signal Processing top 10%
- Digital Filter Design and Implementation 10
- Mathematical Physics top 10%
- Numerical methods in inverse problems 6
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- Advanced Numerical Analysis Techniques 11
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- Approximation Theory and Sequence Spaces 10
- Co-authors
- H. N. MhaskarEwald QuakBernd FischerRalf HielscherDaniel PottsHelmut SchaebenJ. D. WardF. J. Narcowich
- Journals
- Journal of Approximation Theory (8 papers)Journal of Fourier Analysis and Applications (4 papers)Numerical Algorithms (4 papers)
- Partner nations
- GermanyUnited StatesUkraine
In The Last Decade
Jürgen Prestin
58 papers receiving 530 citations
Peers
Comparison fields: 5 of 68
- Applied Mathematics 291
- Numerical Analysis 98
- Computer Vision and Pattern Recognition 208
- Signal Processing 96
- Mathematical Physics 71
Countries citing papers authored by Jürgen Prestin
This map shows the geographic impact of Jürgen Prestin'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 Jürgen Prestin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jürgen Prestin more than expected).
Fields of papers citing papers by Jürgen Prestin
This network shows the impact of papers produced by Jürgen Prestin. 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 Jürgen Prestin. The network helps show where Jürgen Prestin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jürgen Prestin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 1 | |
| 2 | 2021 | 2 | |
| 3 | 2019 | 2 | |
| 4 | 2018 | 0 | |
| 5 | 2018 | 2 | |
| 6 | 2017 | 1 | |
| 7 | 2015 | 2 | |
| 8 | 2012 | 1 | |
| 9 | 2009 | 6 | |
| 10 | 2009 | 13 | |
| 11 | 2008 | 22 | |
| 12 | 2008 | 13 | |
| 13 | 2006 | 1 | |
| 14 | 2006 | 23 | |
| 15 | 1999 | 6 | |
| 16 | On Marcinkiewicz-Zygmund-Type Inequalities | 1997 | 2 |
| 17 | A duality principle for trigonometric wavelets | 1994 | 2 |
| 18 | 1994 | 7 | |
| 19 | 1994 | 2 | |
| 20 | 1990 | 6 |
About Jürgen Prestin
Jürgen Prestin is a scholar working on Applied Mathematics, Numerical Analysis, Statistics and Probability, Signal Processing and Computer Vision and Pattern Recognition, having authored 62 papers that have together received 580 indexed citations. Recurring topics across this work include Mathematical Analysis and Transform Methods (24 papers), Mathematical functions and polynomials (18 papers), Image and Signal Denoising Methods (16 papers), Mathematical Approximation and Integration (11 papers), Advanced Numerical Analysis Techniques (11 papers), Digital Filter Design and Implementation (10 papers), Approximation Theory and Sequence Spaces (10 papers) and Numerical methods in inverse problems (6 papers). The work is most often cited by research in Applied Mathematics (291 citations), Numerical Analysis (98 citations), Computer Vision and Pattern Recognition (208 citations), Signal Processing (96 citations) and Mathematical Physics (71 citations). Jürgen Prestin has collaborated with scholars based in Germany, United States and Ukraine. Frequent co-authors include H. N. Mhaskar, Ewald Quak, Bernd Fischer, Ralf Hielscher, Daniel Potts, Helmut Schaeben, J. D. Ward, F. J. Narcowich, Frank Filbir and Dirk Langemann. Their work appears in journals such as Journal of Approximation Theory, Journal of Fourier Analysis and Applications, Numerical Algorithms, Constructive Approximation and Mathematische Nachrichten.
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.