Demo Data from EDBT 2026 / reviewers in the wild / expert
Yong-Fu Huang
dblp:23/8707
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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.
| Computer networks
1 paper |
Physical-layer communications · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Physical-layer communications › equalization
blind equalization |
0.1 | 1 | 2010 | Blind carrier phase acquisition and tracking for 8-VSB signals · IEEE Trans. Commun. 2010 |
Physical-layer communications › synchronization › carrier recovery
carrier phase recovery |
0.1 | 1 | 2010 | Blind carrier phase acquisition and tracking for 8-VSB signals · IEEE Trans. Commun. 2010 |
Methods — techniques the papers use, named apart from their topics
stochastic gradient descent · 0.1cost function design · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Blind carrier phase acquisition and tracking for 8-VSB signalsabstractA blind carrier phase derotator can be employed to correct and track carrier phase offset either before or after equalization in a blind adaptive receiver. This work proposes a computationally efficient blind carrier offset recovery algorithm for 8-vestigial side-band (8-VSB) signals by designing its cost function such that its cost surface has only two global minima without any undesirable local minima. Consequently, the proposed algorithm is not complicated by the possibility of a stochastic gradient descent (SGD) algorithm converging to a false local minimum, and global convergence can always be ensured. Moreover, the proposed algorithm can adopt a large step size in the transient period to accelerate the convergence speed along with a small step size in the convergence period to reduce the stochastic gradient noise. Jenq-Tay Yuan, Yong-Fu Huang |
IEEE Trans. Commun. | 2 |