D. Mansour
Impact in
- Signal Processing top 5%
- Speech and Audio Processing
- Blind Source Separation Techniques
- Computational Mechanics top 5%
- Advanced Adaptive Filtering Techniques
- Advanced Numerical Methods in Computational Mathematics
Papers in
-
- Advanced Adaptive Filtering Techniques 6
- Advanced Numerical Methods in Computational Mathematics 3
-
- Speech and Audio Processing 4
- Blind Source Separation Techniques 3
- Co-authors
- Alfred Gray (2 shared papers)Christian Lubich (3 shared papers)Chandrasekhar Venkataraman (1 shared paper)Gerhard Dziuk (1 shared paper)D. Hertz (1 shared paper)S.A. Mazen (1 shared paper)J. Markel (1 shared paper)
- Journals
- IMA Journal of Numerical Analysis (2 papers)Numerische Mathematik (1 paper)Mathematics of Computation (1 paper)Journal of Computational and Applied Mathematics (1 paper)IEEE Transactions on Circuits and Systems (1 paper)
- Partner nations
- GermanyIsraelUnited States
In The Last Decade
D. Mansour
9 papers receiving 250 citations
Peers
Comparison fields: 5 of 34
- Signal Processing 158
- Computational Mechanics 232
- Numerical Analysis 47
- Computational Theory and Mathematics 36
- Computer Vision and Pattern Recognition 35
Countries citing papers authored by D. Mansour
This map shows the geographic impact of D. Mansour'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 D. Mansour with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Mansour more than expected).
Fields of papers citing papers by D. Mansour
This network shows the impact of papers produced by D. Mansour. 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 D. Mansour. The network helps show where D. Mansour may publish in the future.
Co-authors
The 7 scholars most cited alongside D. Mansour, 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 | 1982 | 167 | |
| 2 | 2013 | 49 | |
| 3 | 2011 | 26 | |
| 4 | 2014 | 11 | |
| 5 | 2014 | 6 | |
| 6 | 2005 | 5 | |
| 7 | 1986 | 3 | |
| 8 | 2005 | 1 | |
| 9 | 2005 | 1 | |
| 10 | 2024 | 0 | |
| 11 | 2005 | 0 |
About D. Mansour
D. Mansour is a scholar working on Computational Mechanics, Signal Processing, Numerical Analysis, Control and Systems Engineering and Computational Theory and Mathematics, having authored 11 papers that have together received 269 indexed citations. Recurring topics across this work include Advanced Adaptive Filtering Techniques (6 papers), Speech and Audio Processing (4 papers), Numerical methods for differential equations (3 papers), Advanced Numerical Methods in Computational Mathematics (3 papers), Blind Source Separation Techniques (3 papers), Electromagnetic Simulation and Numerical Methods (2 papers), Differential Equations and Numerical Methods (2 papers) and Advanced Mathematical Modeling in Engineering (2 papers). The work is most often cited by research in Signal Processing (158 citations), Computational Mechanics (232 citations), Numerical Analysis (47 citations), Computational Theory and Mathematics (36 citations) and Computer Vision and Pattern Recognition (35 citations). D. Mansour has collaborated with scholars based in Germany, Israel and United States. Frequent co-authors include Alfred Gray, Christian Lubich, Chandrasekhar Venkataraman, Gerhard Dziuk, D. Hertz, S.A. Mazen and J. Markel. Their work appears in journals such as IMA Journal of Numerical Analysis, Numerische Mathematik, Mathematics of Computation, Journal of Computational and Applied Mathematics 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.