1063-5203
Published by: Elsevier
https://www.journals.elsevier.com/applied-and-computational-harmonic-analysis
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 63 | 61 | 92 | 21 |
| Computer Science | 404 | 29 | 41 | 15 |
Applied and Computational Harmonic Analysis focuses largely on the fields of Mathematical analysis, Wavelet, Algorithm, Discrete mathematics and Pure mathematics. It holds forums on Mathematical analysis that merges themes from other disciplines such as Function (mathematics), Eigenvalues and eigenvectors, Scaling and Applied mathematics. The journal links adjacent topics like Wavelet with Orthonormal basis.
The journal centers on topics in Algorithm, with a focus on Compressed sensing. It features studies on Compressed sensing, including topics such as Restricted isometry property. The concepts on Discrete mathematics presented in it can also apply to other research fields, including Multiresolution analysis and Combinatorics.
Applied and Computational Harmonic Analysis focuses on Combinatorics as well as the interrelated topic of Matrix (mathematics). In particular, the Discrete wavelet transform works presented emphasize discussions on Second-generation wavelet transform. It concentrates on Wavelet transform topics that focus on Cascade algorithm and Harmonic wavelet transform.
The most cited articles investigate studies in Wavelet, Algorithm, Mathematical analysis, Discrete mathematics and Compressed sensing. Most of the Wavelet studies addressed in the most cited articles also intersect with Pure mathematics. While the published papers focused on Algorithm, they were also able to explore topics like Frame (networking), Signal, Artificial intelligence and Phase retrieval.
The foci of the journal are Pure mathematics, Function (mathematics), Combinatorics, Applied mathematics and Algorithm. Issues in Pure mathematics were discussed, taking into consideration concepts from other disciplines like Mellin transform, Quantization (signal processing) and Complex plane. The Function (mathematics) research presented in Applied and Computational Harmonic Analysis explores the relationship between Lipschitz continuity and the closely related topic of Extrapolation, Optimization problem, Auxiliary function and Differentiable function.
The studies on Combinatorics discussed can also contribute to research in the domains of Minification, Matrix (mathematics), Sparse vector, Radius and Chebyshev polynomials. The studies in Applied mathematics featured incorporate elements of Adjacency matrix, Elliptic operator, Limit (mathematics) and Cluster analysis. Applied and Computational Harmonic Analysis focuses on Algorithm but the discussions also offer insight into other areas such as Low-rank approximation, Rank (linear algebra), Hankel matrix, Toeplitz matrix and Piecewise.
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 Applied and Computational Harmonic Analysis (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 Applied and Computational Harmonic Analysis (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 2022 edition, 6.67% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 14.29% 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 35.71% 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.
Ding-Xuan Zhou
(2020)Unknown
(2020)Milan Korda;Mihai Putinar;Mihai Putinar;Igor Mezić
(2020)Unknown
(2021)Junhong Lin;Alessandro Rudi;Alessandro Rudi;Lorenzo Rosasco;Lorenzo Rosasco;Lorenzo Rosasco;Volkan Cevher
(2020)Matthew M. Dunlop;Dejan Slepčev;Andrew M. Stuart;Matthew Thorpe
(2020)Wei Chen;Wei Chen;Zunwei Fu;Loukas Grafakos;Yue Wu
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