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D. Gazelle

dblp:97/2892 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1997
—ORCID · none

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

Theory of computation · 1 · 1 first-author

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 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › error-correcting codes
block codes
0.011997
Reliability-based code-search algorithms for maximum-likelihood decoding of block codes · IEEE Trans. Inf. Theory 1997
Coding theory
channel coding
0.011997
Reliability-based code-search algorithms for maximum-likelihood decoding of block codes · IEEE Trans. Inf. Theory 1997
Coding theory › error-correcting codes › block codes
linear block codes
0.011997
Reliability-based code-search algorithms for maximum-likelihood decoding of block codes · IEEE Trans. Inf. Theory 1997
Coding theory › error-correcting codes › decoding › decoding algorithms › optimal decoding
maximum-likelihood decoding
0.011997
Reliability-based code-search algorithms for maximum-likelihood decoding of block codes · IEEE Trans. Inf. Theory 1997
Coding theory › error-correcting codes › decoding › decoding algorithms
reliability-based decoding
0.011997
Reliability-based code-search algorithms for maximum-likelihood decoding of block codes · IEEE Trans. Inf. Theory 1997

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

reliability information · 0.0information set decoding · 0.0
YearPublicationVenuePosition
1997 Reliability-based code-search algorithms for maximum-likelihood decoding of block codes
abstract
Efficient code-search maximum-likelihood decoding algorithms, based on reliability information, are presented for binary Linear block codes. The codewords examined are obtained via encoding. The information set utilized for encoding comprises the positions of those columns of a generator matrix G of the code which, for a given received sequence, constitute the most reliable basis for the column space of G. Substantially reduced computational complexity of decoding is achieved by exploiting the ordering of the positions within this information set. The search procedures do not require memory; the codeword to be examined is constructed from the previously examined codeword according to a fixed rule. Consequently, the search algorithms are applicable to codes of relatively large size. They are also conveniently modifiable to achieve efficient nearly optimum decoding of particularly large codes.
D. Gazelle, Jakov Snyders
IEEE Trans. Inf. Theory1