EDBT 2026 Demo / reviewers in the wild / expert
Stephen A. Norman
dblp:81/5839
· 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 · 67% Information theory · 33% | |
| Computer networks
1 paper |
Physical-layer communications · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › error-correcting codes › code construction › optimal code construction
minimum distance maximization |
0.0 | 1 | 1991 | Optimization of signal sets for partial-response channels - I: Numerical techniques · IEEE Trans. Inf. Theory 1991 |
Information theory › communication channels › channel models › channels with memory
partial-response channel |
0.0 | 1 | 1991 | Optimization of signal sets for partial-response channels - I: Numerical techniques · IEEE Trans. Inf. Theory 1991 |
Coding theory › signal sets
signal set design |
0.0 | 1 | 1991 | Optimization of signal sets for partial-response channels - I: Numerical techniques · IEEE Trans. Inf. Theory 1991 |
Physical-layer communications
power constraint |
0.0 | 1 | 1991 | Optimization of signal sets for partial-response channels - I: Numerical techniques · IEEE Trans. Inf. Theory 1991 |
Methods — techniques the papers use, named apart from their topics
gradient-based optimization · 0.0dense lattices · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1991 | Optimization of signal sets for partial-response channels - I: Numerical techniquesabstractGiven a linear, time-invariant, discrete-time channel, the problem of constructing N input signals of finite length K that maximize minimum l/sub 2/ distance between pairs of outputs is considered. Two constraints on the input signals are considered: a power constraint on each of the N inputs (hard constraint) and an average power constraint over the entire set of inputs (soft constraint). The hard constraint, problem is equivalent to packing N points in an ellipsoid in min(K,N-1) dimensions to maximize the minimum Euclidean distance between pairs of points. Gradient-based numerical algorithms and a constructive technique based on dense lattices are used to find locally optimal solutions to the preceding signal design problems. Two numerical examples are shown for which the average spectrum of an optimized signal set resembles the water pouring spectrum that achieves Shannon capacity, assuming additive white Gaussian noise.> Michael L. Honig, Kenneth Steiglitz, Stephen A. Norman |
IEEE Trans. Inf. Theory | 3 |