J
Junan Zhang
Researcher at Duke University
Publications - 36
Citations - 1647
Junan Zhang is an academic researcher from Duke University. The author has contributed to research in topics: Tomosynthesis & Redundancy (information theory). The author has an hindex of 20, co-authored 36 publications receiving 1562 citations. Previous affiliations of Junan Zhang include University of California, San Diego & University of California, Los Angeles.
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Journal ArticleDOI
Stopping set distribution of LDPC code ensembles
TL;DR: Several results on the asymptotic behavior of stopping sets in Tanner-graph ensembles are derived, including an expression for the normalized average stopping set distribution, yielding a critical fraction of the block length above which codes have exponentially many stopping sets of that size.
Journal ArticleDOI
Universal compression of memoryless sources over unknown alphabets
TL;DR: It is shown that the patterns of i.i.d. strings over all, including infinite and even unknown, alphabets, can be compressed with diminishing redundancy, both in block and sequentially, and that the compression can be performed in linear time.
Proceedings ArticleDOI
Always Good Turing: asymptotically optimal probability estimation
TL;DR: The attenuation of a probability estimator is defined as the largest possible ratio between the per-symbol probability assigned to an arbitrarily-long sequence by any distribution, and the corresponding probability assigned by the estimator.
Journal ArticleDOI
Always Good Turing: asymptotically optimal probability estimation.
TL;DR: In this paper, the authors define the attenuation of a probability estimator as the largest possible ratio between the per-symbol probability assigned to an arbitrarily long sequence by any distribution, and the corresponding probability assigned by the estimator.
Proceedings ArticleDOI
Stopping sets and the girth of Tanner graphs
TL;DR: This work considers the size of the smallest stopping set in any bipartite graph of girth g and left degree d, and bounds it in terms of d, showing that for fixed d, /spl sigma/(d,g) grows exponentially with g.