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Yuval Domb

dblp:37/10826 · DBLP profile ↗
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3ranked-venue papers
3as first author
0since 2021 · last 2016
—ORCID · none

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

Theory of computation · 2 · 2 first-authorApplied, interdisciplinary, general and emerging computing · 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
2 papers
Coding theory · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory
lattice codes
0.522016
The Random Coding Bound Is Tight for the Average Linear Code or Lattice · IEEE Trans. Inf. Theory 2016
Non-Random Coding Error Bounds for Lattices · IEEE Trans. Inf. Theory 2016
Coding theory
channel coding
0.212016
Non-Random Coding Error Bounds for Lattices · IEEE Trans. Inf. Theory 2016
Coding theory › channel coding
error exponent
0.212016
Non-Random Coding Error Bounds for Lattices · IEEE Trans. Inf. Theory 2016
Coding theory › channel coding
error probability bounds
0.212016
Non-Random Coding Error Bounds for Lattices · IEEE Trans. Inf. Theory 2016
Coding theory › error-correcting codes › block codes
linear code
0.212016
The Random Coding Bound Is Tight for the Average Linear Code or Lattice · IEEE Trans. Inf. Theory 2016
Coding theory › channel coding › error probability bounds
random coding bound
0.212016
The Random Coding Bound Is Tight for the Average Linear Code or Lattice · IEEE Trans. Inf. Theory 2016

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

random ensemble analysis · 0.2minkowski-hlawka theorem · 0.2expurgation · 0.2distance spectrum · 0.2
YearPublicationVenuePosition
2016 Non-Random Coding Error Bounds for Lattices
abstract
An upper bound on the error probability of specific lattices, based on their distance spectrum, is constructed. The derivation is accomplished using a simple alternative to the Minkowski-Hlawka mean-value theorem of the geometry of numbers. In many ways, the new bound greatly resembles the Shulman-Feder bound for linear codes. Based on the new bound, error-exponent and channel-dispersion expressions are derived for specific lattice sequences (of increasing dimension) over the AWGN channel. Measuring a sequence's gap to capacity, using the new asymptotics, is demonstrated. Additional finite dimension results, encountered along the way, are presented.
Yuval Domb, Meir Feder
IEEE Trans. Inf. Theory1
2016 The Random Coding Bound Is Tight for the Average Linear Code or Lattice
abstract
In 1973, Gallager proved that the random-coding bound is exponentially tight for the random code ensemble at all rates, even below expurgation. This result explained that the random-coding exponent does not achieve the expurgation exponent due to the properties of the random ensemble, irrespective of the utilized bounding technique. It has been conjectured that this same behavior holds true for a random ensemble of linear codes. This conjecture is proved in this paper. In addition, it is shown that this property extends to Poltyrev's random-coding exponent for a random ensemble of lattices.
Yuval Domb, Ram Zamir, Meir Feder
IEEE Trans. Inf. Theory1
2012 Non-random coding error exponent for lattices
abstract
An upper bound on the error probability of specific lattices, based on their distance spectrum, is constructed. The derivation is accomplished using a simple alternative to the Minkowski-Hlawka mean-value theorem of the geometry of numbers. In many ways, the new bound greatly resembles the Shulman-Feder bound for linear codes. Based on the new bound, an error exponent is derived for specific lattice sequences (of increasing dimension) over the AWGN channel. Measuring the sequence's gap to capacity, using the new exponent, is demonstrated.
Yuval Domb, Meir Feder
ISIT1