Signal Processing

434.1k papers and 7.2M indexed citations i.

About

434.1k papers covering Signal Processing have received a total of 7.2M indexed citations since 1950. Papers on subfields are most often about the specific topic of Speech and Audio Processing, Data Management and Algorithms and Blind Source Separation Techniques and also cover the fields of Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. Papers citing papers on subfields are usually about Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience. Some of the most active scholars covering Signal Processing are Hirotugu Akaike, Geoffrey E. Hinton, Stephen Boyd, Peter J. Rousseeuw, Laurens van der Maaten, Scott Makeig, Anil K. Jain, Vladimir Vapnik, Aapo Hyvärinen and Arnaud Delorme.

In The Last Decade

Fields of papers citing papers about Signal Processing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers covering Signal Processing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers covering Signal Processing.

Countries where authors publish papers about Signal Processing

Since Specialization
Citations

This map shows the geographic impact of research in Signal Processing. 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 about Signal Processing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Signal Processing 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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2025