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

F. S. Chang

dblp:272/5835 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
0since 2021 · last 1976
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 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.

Computer networks
1 paper
Physical-layer communications · 60% Internet of things and sensor networks · 20% Wireless sensing and localization · 20%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wireless sensing and localization › tracking
bayesian tracking
0.011976
Target Tracking Over Fading Channels · IEEE Trans. Commun. 1976
Physical-layer communications
channel modeling
0.011976
Target Tracking Over Fading Channels · IEEE Trans. Commun. 1976
Physical-layer communications
fading channels
0.011976
Target Tracking Over Fading Channels · IEEE Trans. Commun. 1976
Physical-layer communications
signal processing for communications
0.011976
Target Tracking Over Fading Channels · IEEE Trans. Commun. 1976
Internet of things and sensor networks › wireless sensor network
target tracking
0.011976
Target Tracking Over Fading Channels · IEEE Trans. Commun. 1976

Methods — techniques the papers use, named apart from their topics

mean-square error analysis · 0.0
YearPublicationVenuePosition
1976 Target Tracking Over Fading Channels
abstract
The problem of tracking a target in a multitarget environment when the observations are received over a fading channel is considered. The optimal Bayes solution to the tracking problem in such cases involves growing memory and hence is not feasible. A particularly effective suboptimal scheme uses a probabilistic judgment at each stage of the observations to overcome this problem. This concise paper presents an evaluation of the scheme in terms of mean-square error performance when the observations are received over fading channels.
F. S. Chang, Mandyam D. Srinath
IEEE Trans. Commun.1