Strong Typicality is a formal concept in information theory that characterizes a set of sequences in which the empirical frequency of each symbol converges exactly to its prescribed probability mass function, thereby distinguishing it from other typicality notions by imposing strict uniformity in symbol occurrence rates.
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113
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79
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2017–2026
7
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Publications
56
1–5 of 56
Authors
113
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1–5 of 113
Institutions
79
University of California, Berkeley
Berkeley, United States
3 h-index
3 publications
605 citations
Hungarian Academy of Sciences
Budapest, Hungary
2 h-index
4 publications
420 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
2 h-index
2 publications
40 citations
Durham University
Durham, United Kingdom
2 h-index
4 publications
240 citations
University of Toledo
Toledo, United States
2 h-index
2 publications
210 citations
University of Pennsylvania
Philadelphia, United States
2 h-index
7 publications
426 citations
Texas Christian University
Fort Worth, United States
2 h-index
4 publications
110 citations
University of Illinois Urbana-Champaign
Urbana, United States
2 h-index
2 publications
112 citations
1–8 of 79
Venues
- Memory & Cognition
5 publications · 354 citations
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- Journal of Experimental Psychology Learning Memory and Cognition
2 publications · 321 citations
2
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- Journal of Experimental Psychology Human Learning & Memory
2 publications · 87 citations
2
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- IEEE Transactions on Information Theory
2 publications · 50 citations
2
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- Journal of Experimental Psychology Human Perception & Performance
2 publications · 560 citations
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