Demo Data from EDBT 2026 / reviewers in the wild / expert
Fei Yue
dblp:162/8535
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › sequences › sequence design
optical orthogonal codes |
0.2 | 1 | 2015 | Multilength Optical Orthogonal Codes: New Upper Bounds and Optimal Constructions · IEEE Trans. Inf. Theory 2015 |
Coding theory › error-correcting codes › coding bounds
code size bounds |
0.1 | 1 | 2015 | Multilength Optical Orthogonal Codes: New Upper Bounds and Optimal Constructions · IEEE Trans. Inf. Theory 2015 |
Methods — techniques the papers use, named apart from their topics
intracross correlation · 0.2autocross correlation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Multilength Optical Orthogonal Codes: New Upper Bounds and Optimal ConstructionsabstractLet N={n0, n1, ... , nk-1} be a set of positive integers and M= {m0, m1, ... , mk-1} be a multiset of positive integers. By an (N, M, w,1; λ)-multilength optical orthogonal code (MLOOC), we mean an MLOOC of autocross correlation value and intracross correlation value one and intercross correlation value λ. The code contains micodewords of weight w and length nifor 0 ≤ i ≤ k-1. The study of MLOOCs is motivated by an application in optical networks requiring multiple signaling rates and quality-of-services. In this paper, we study (N, M, w,1; λ)-MLOOCs with λ =2 (the least value among the nontrivial intercross correlations). Some new upper bounds on code size are derived under certain restrictions and a novel encoding approach is established. A number of series of new MLOOCs are then produced. These codes are of optimal sizes with respect to the new bounds. Xizhao Luo, Jianxing Yin, Fei Yue |
IEEE Trans. Inf. Theory | 3 |