EDBT 2026 Demo / reviewers in the wild / expert
F. Y. Lin
dblp:19/2995
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1991
—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 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory
source coding |
0.0 | 1 | 1991 | Performance of entropy-constrained block transform quantizers · IEEE Trans. Inf. Theory 1991 |
Coding theory › source coding
transform coding |
0.0 | 1 | 1991 | Performance of entropy-constrained block transform quantizers · IEEE Trans. Inf. Theory 1991 |
Coding theory › source coding › quantization
entropy-constrained quantization |
0.0 | 1 | 1991 | Performance of entropy-constrained block transform quantizers · IEEE Trans. Inf. Theory 1991 |
Coding theory › source coding
rate-distortion theory |
0.0 | 1 | 1991 | Performance of entropy-constrained block transform quantizers · IEEE Trans. Inf. Theory 1991 |
Methods — techniques the papers use, named apart from their topics
uniform threshold quantization · 0.0asymptotic analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1991 | Performance of entropy-constrained block transform quantizersabstractAn analysis of the rate-distortion performance of an entropy-constrained block transform quantization scheme operating on first-order stationary Gauss-Markov sources is presented. Uniform threshold quantization is employed to quantize the transform coefficients. An algorithm for optimum stepsize (or, equivalently, entropy) assignment among the quantizers is developed and a simple asymptotic formula indicating the high-rate performance of the block transform quantization scheme is presented. Specific results determining the rate-distortion performance of the entropy-constrained block transform quantization scheme operating upon first-order Gauss-Markov sources are presented, and comparisons are made with the Huang and Schultheiss (1963) block transform quantization, vector quantization, and predictive quantization.> Nariman Farvardin, F. Y. Lin |
IEEE Trans. Inf. Theory | 2 |