Demo Data from VLDB 2026 / reviewers in the wild / expert
Gary L. Fillmore
dblp:134/4246
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1969
—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 |
Information theory · 56% Coding theory · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information theory › channel capacity
information rate |
0.0 | 1 | 1969 | Information rates for photocount detection systems · IEEE Trans. Inf. Theory 1969 |
Coding theory
optical communication |
0.0 | 1 | 1969 | Information rates for photocount detection systems · IEEE Trans. Inf. Theory 1969 |
Information theory
channel capacity |
0.0 | 1 | 1969 | Information rates for photocount detection systems · IEEE Trans. Inf. Theory 1969 |
Methods — techniques the papers use, named apart from their topics
coherent state model · 0.0additive gaussian noise · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1969 | Information rates for photocount detection systemsabstractA model that allows one to calculate information rates for optical communication systems that use photocount detection is presented. This model has its basis in the coherent states of the field. It consists of a source that places the field in a coherent state, a channel that can introduce additive Gaussian noise, and a photodetector that produces the number of photocounts in the detection interval as output symbols. The capability of introducing additive Gaussian noise can also be used to represent a physical source. The model is applied to several examples to illustrate its use. The rate of flow of information through the channel is calculated for a binary channel with and without additive Gaussian noise. The information rate for a noiseless channel is also obtained for the case in which the signals sent by a single-mode coherent source are selected from a Gaussian distribution. Gary L. Fillmore, Gerard Lachs |
IEEE Trans. Inf. Theory | 1 |