The L-curve and its use in the numerical treatment of inverse problems
- Authors
- Per Christian Hansen
In The Last Decade
doi.org/w75350163 →Countries where authors are citing The L-curve and its use in the numerical treatment of inverse problems
This map shows the geographic impact of The L-curve and its use in the numerical treatment of inverse problems. 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 The L-curve and its use in the numerical treatment of inverse problems with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites The L-curve and its use in the numerical treatment of inverse problems more than expected).
Fields of papers citing The L-curve and its use in the numerical treatment of inverse problems
This network shows the impact of The L-curve and its use in the numerical treatment of inverse problems. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the The L-curve and its use in the numerical treatment of inverse problems.
About The L-curve and its use in the numerical treatment of inverse problems
This paper, published in 2000, received 537 indexed citations . Written by Per Christian Hansen covering the research area of Mathematical Physics, Applied Mathematics and Biomedical Engineering. It is primarily cited by scholars working on Mathematical Physics (116 citations), Radiology, Nuclear Medicine and Imaging (97 citations) and Mechanics of Materials (92 citations).
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.
This paper is also available at doi.org/w75350163.