Entropy in Data Compression is a theoretical construct in information theory that quantifies the minimum average number of bits required to losslessly encode information from a source, based on the statistical distribution of its symbols, thereby establishing a fundamental limit on data compression efficiency.
205
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14.4K
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400
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231
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Publications per year
2017–2026
34
Parents
Publications
205
Opportunistic data structures with applications
Paolo Ferragina, Giovanni Manzini · 2002 · 1.1K citations
Asymptotically efficient quantizing
H. Gish, John R. Pierce · IEEE Transactions on Information Theory · 1968 · 470 citations
Sergio Verdú · IEEE Transactions on Information Theory · 1998 · 321 citations
1–5 of 205
Authors
400
- JZ
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- RG
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- JS
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1–5 of 400
Institutions
231
University of Pisa
Pisa, Italy
11 h-index
12 publications
2.6K citations
Technion – Israel Institute of Technology
Haifa, Israel
11 h-index
17 publications
1.1K citations
Purdue University West Lafayette
West Lafayette, United States
9 h-index
12 publications
1.1K citations
Princeton University
Princeton, United States
8 h-index
12 publications
627 citations
University of California, Berkeley
Berkeley, United States
7 h-index
10 publications
290 citations
University of Chile
Santiago, Chile
5 h-index
6 publications
278 citations
Centre National de la Recherche Scientifique
Paris, France
5 h-index
10 publications
689 citations
AT&T (United States)
Bedminster, United States
5 h-index
6 publications
770 citations
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Venues
- IEEE Transactions on Information Theory
29 publications · 6.1K citations
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- Entropy
5 publications · 230 citations
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- IEEE Transactions on Image Processing
4 publications · 162 citations
4
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- arXiv (Cornell University)
Repository · 3 publications · 80 citations
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- IEEE Transactions on Circuits and Systems for Video Technology
3 publications · 106 citations
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