1930-8337
Published by: American Institute of Mathematical Sciences
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 206 | 42 | 77 | 12 |
Inverse Problems and Imaging tackles a plethora of topics, such as Mathematical analysis, Inverse problem, Algorithm, Applied mathematics and Regularization (mathematics). The work on Mathematical analysis tackled in Inverse Problems and Imaging brings together disciplines like Scattering, Boundary (topology) and Inverse. While Boundary (topology) is the focus of it, it also provided insights into the studies of Stability (probability), Boundary value problem and Domain (mathematical analysis).
In Inverse Problems and Imaging, Electrical impedance tomography, Bounded function, Mathematical optimization, Wave equation and Nonlinear system are investigated in conjunction with one another to address concerns in Inverse problem research. It focuses on Algorithm but the discussions also offer insight into other areas such as Noise reduction, Iterative reconstruction and Minification. The majority of Regularization (mathematics) studies are focused on the issues of Tikhonov regularization.
Many of the studies tackled connect Inverse scattering problem with a similar field of study like Near and far field.
The main points discussed in the journal papers deal with Mathematical analysis, Inverse problem, Algorithm, Mathematical optimization and Applied mathematics. In addition to Mathematical analysis research, the most cited publications aim to explore topics under Boundary (topology), Inverse and Eigenvalues and eigenvectors. The works on Inverse problem tackled in the journal papers bring together disciplines like Electrical impedance tomography, Tomography, Uniqueness, Nonlinear system and Domain (mathematical analysis).
Inverse Problems and Imaging primarily focuses on research topics in Inverse problem, Mathematical analysis, Applied mathematics, Algorithm and Inverse. While Inverse problem is the key highlight in Inverse Problems and Imaging, it also covered some subjects on Helmholtz equation and Fourier transform. The journal facilitates discussions on Mathematical analysis that incorporate concepts from other fields like Boundary (topology) and Eigenvalues and eigenvectors.
Applied mathematics is the main point of discussion in the journal but it also connects with fields such as
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Inverse Problems and Imaging (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Inverse Problems and Imaging (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 81.82% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 28.57% were posted by at least one author from the top 10 institutions publishing in the journal. Another 7.14% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.43% of all publications and 42.86% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Ke Wei;Jianfeng Cai;Tony Fan-cheong Chan;Shing Yu Leung
(2020)Meng Ding;Ting-Zhu Huang;Xi-Le Zhao;Michael K. Ng
(2021)Bao Wang;Alex Lin;Penghang Yin;Wei Zhu
(2021)Barbara Kaltenbacher;William Rundell
(2021)Markus Haltmeier;A. Leitao;Otmar Scherzer
(2020)Michael V. Klibanov;Thuy T. Le;Loc H. Nguyen;Anders Sullivan
(2021)Deyue Zhang;Yukun Guo;Fenglin Sun;Hongyu Liu
(2020)Youjun Deng;Yan Jiang;Hongyu Liu;Kai Zhang
(2021)Alexey V. Smirnov;Michael V. Klibanov;Loc H. Nguyen
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