Applied and Computational Harmonic Analysis

1.5k papers and 48.4k indexed citations i.

About

The 1.5k papers published in Applied and Computational Harmonic Analysis in the last decades have received a total of 48.4k indexed citations. Papers published in Applied and Computational Harmonic Analysis usually cover Computer Vision and Pattern Recognition (777 papers), Applied Mathematics (688 papers) and Computational Mechanics (504 papers) specifically the topics of Image and Signal Denoising Methods (665 papers), Mathematical Analysis and Transform Methods (621 papers) and Sparse and Compressive Sensing Techniques (311 papers). The most active scholars publishing in Applied and Computational Harmonic Analysis are Ronald R. Coifman, Joel A. Tropp, Deanna Needell, Wim Sweldens, David L. Donoho, Stéphane Lafon, Ingrid Daubechies, Nick Kingsbury, Mike E. Davies and Hau‐Tieng Wu.

In The Last Decade

Fields of papers published in Applied and Computational Harmonic Analysis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Applied and Computational Harmonic Analysis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Applied and Computational Harmonic Analysis.

Countries where authors publish in Applied and Computational Harmonic Analysis

Since Specialization
Citations

This map shows the geographic impact of research published in Applied and Computational Harmonic Analysis. 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 papers published in Applied and Computational Harmonic Analysis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Applied and Computational Harmonic Analysis more than expected).

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.

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