Near Shannon limit error-correcting coding and decoding
Impact in
Classified as
- Authors
- Claude Berrou
- Journal
- Medical Entomology and Zoology
In The Last Decade
doi.org/w93370397 →Countries where authors are citing Near Shannon limit error-correcting coding and decoding
This map shows the geographic impact of Near Shannon limit error-correcting coding and decoding. 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 Near Shannon limit error-correcting coding and decoding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Near Shannon limit error-correcting coding and decoding more than expected).
Fields of papers citing Near Shannon limit error-correcting coding and decoding
This network shows the impact of Near Shannon limit error-correcting coding and decoding. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Near Shannon limit error-correcting coding and decoding.
About Near Shannon limit error-correcting coding and decoding
This paper, published in 1993, received 565 indexed citations . Written by Claude Berrou covering the research area of Computer Networks and Communications, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. It is primarily cited by scholars working on Computer Networks and Communications (493 citations), Electrical and Electronic Engineering (491 citations), Artificial Intelligence (178 citations), Computational Theory and Mathematics (51 citations) and Signal Processing (26 citations). Published in Medical Entomology and Zoology.
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/w93370397.