Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Yong-Fu Huang

dblp:23/8707 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Physical-layer communications › equalization
blind equalization
0.112010
Blind carrier phase acquisition and tracking for 8-VSB signals · IEEE Trans. Commun. 2010
Physical-layer communications › synchronization › carrier recovery
carrier phase recovery
0.112010
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
YearPublicationVenuePosition
2010 Blind carrier phase acquisition and tracking for 8-VSB signals
abstract
A 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