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Gregory J. Nelson

dblp:74/3041 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Coding theory · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › source coding
lossless compression
0.012000
Universal lossless compression via multilevel pattern matching · IEEE Trans. Inf. Theory 2000
Coding theory
source coding
0.012000
Universal lossless compression via multilevel pattern matching · IEEE Trans. Inf. Theory 2000
Coding theory › source coding
universal coding
0.012000
Universal lossless compression via multilevel pattern matching · IEEE Trans. Inf. Theory 2000
Coding theory › source coding › source modeling
finite-state sources
0.012000
Universal lossless compression via multilevel pattern matching · IEEE Trans. Inf. Theory 2000

Methods — techniques the papers use, named apart from their topics

parallel substitution · 0.0arithmetic coding · 0.0
YearPublicationVenuePosition
2000 Universal lossless compression via multilevel pattern matching
abstract
A universal lossless data compression code called the multilevel pattern matching code (MPM code) is introduced. In processing a finite-alphabet data string of length n, the MPM code operates at O(log log n) levels sequentially. At each level, the MPM code detects matching patterns in the input data string (substrings of the data appearing in two or more nonoverlapping positions). The matching patterns detected at each level are of a fixed length which decreases by a constant factor from level to level, until this fixed length becomes one at the final level. The MPM code represents information about the matching patterns at each level as a string of tokens, with each token string encoded by an arithmetic encoder. From the concatenated encoded token strings, the decoder can reconstruct the data string via several rounds of parallel substitutions. A O(1/log n) maximal redundancy/sample upper bound is established for the MPM code with respect to any class of finite state sources of uniformly bounded complexity. We also show that the MPM code is of linear complexity in terms of time and space requirements. The results of some MPM code compression experiments are reported.
John C. Kieffer, En-Hui Yang, Gregory J. Nelson, Pamela C. Cosman
IEEE Trans. Inf. Theory3