EDBT 2026 Demo / reviewers in the wild / expert
Albert Groenenboom
dblp:80/1347
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2002
—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 |
Information theory · 70% Coding theory · 30% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › channel coding
error probability bounds |
0.0 | 1 | 2002 | A sharp upper bound for the probability of error of the likelihood ratio test for detecting signals in white Gaussian noise · IEEE Trans. Inf. Theory 2002 |
Information theory › hypothesis testing
likelihood ratio test |
0.0 | 1 | 2002 | A sharp upper bound for the probability of error of the likelihood ratio test for detecting signals in white Gaussian noise · IEEE Trans. Inf. Theory 2002 |
Information theory › hypothesis testing
signal detection |
0.0 | 1 | 2002 | A sharp upper bound for the probability of error of the likelihood ratio test for detecting signals in white Gaussian noise · IEEE Trans. Inf. Theory 2002 |
Information theory › channel capacity
additive noise channel |
0.0 | 1 | 2002 | A sharp upper bound for the probability of error of the likelihood ratio test for detecting signals in white Gaussian noise · IEEE Trans. Inf. Theory 2002 |
Methods — techniques the papers use, named apart from their topics
likelihood ratio test · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2002 | A sharp upper bound for the probability of error of the likelihood ratio test for detecting signals in white Gaussian noiseabstractA new sharp upper bound for the probability of error of the likelihood ratio test is given for the detection in white Gaussian noise of any random vector whose norm is greater than, or equal to, a given value and whose probability of presence is less than, or equal to, one half. Also, a new test for the detection of such vectors is described. This test does not depend on the distribution of the signal vector but nevertheless its probability of error is less than, or equal to, the given upper bound. Dominique Pastor, Roger Gay, Albert Groenenboom |
IEEE Trans. Inf. Theory | 3 |