EDBT 2026 Demo / reviewers in the wild / expert
Akira Kishimoto
dblp:271/7345
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1980
—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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Physical-layer communications › hardware impairments
nonlinear amplifier |
0.0 | 1 | 1980 | Signal-to-Noise Ratio of the nth Law Amplifier for Non-Gaussian Noise · IEEE Trans. Commun. 1980 |
Physical-layer communications
signal-to-noise ratio improvement |
0.0 | 1 | 1980 | Signal-to-Noise Ratio of the nth Law Amplifier for Non-Gaussian Noise · IEEE Trans. Commun. 1980 |
Physical-layer communications › signal processing for communications › statistical signal processing
non-gaussian noise |
0.0 | 1 | 1980 | Signal-to-Noise Ratio of the nth Law Amplifier for Non-Gaussian Noise · IEEE Trans. Commun. 1980 |
Methods — techniques the papers use, named apart from their topics
improvement factor analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1980 | Signal-to-Noise Ratio of the nth Law Amplifier for Non-Gaussian NoiseabstractThe effects of thenth law amplifier on signal-to-noise ratio has not been represented as a function of the input signal-to-noise ratio when the input of the nonlinear device contains nonGaussian noise. In this paper, we analyze these effects and determine the improvement factor represented by the ratio of the output SNR to the input SNR. The results are illustrated by the calculation of the improvement factor for the cases where the input noise amplitude distributions are the uniform distribution, the triangle distribution, and the Rician distribution. Masanori Shinriki, Akira Kishimoto, Iwao Sasase, Shinsaku Mori |
IEEE Trans. Commun. | 2 |