Demo Data from EDBT 2026 / reviewers in the wild / expert
Avital Kleiman
dblp:306/2576
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0002-9670-0014ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021
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 graphics and multimedia
1 paper |
Audio and music processing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Audio and music processing
beamforming |
0.6 | 1 | 2022 | Constant-Beamwidth Beamforming With Nonuniform Concentric Ring Arrays · IEEE ACM Trans. Audio Speech Lang. Process. 2022 |
Audio and music processing
microphone array processing |
0.6 | 1 | 2022 | Constant-Beamwidth Beamforming With Nonuniform Concentric Ring Arrays · IEEE ACM Trans. Audio Speech Lang. Process. 2022 |
Methods — techniques the papers use, named apart from their topics
directivity factor maximization · 0.6convex optimization · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Constant-Beamwidth Beamforming With Nonuniform Concentric Ring ArraysabstractSolutions for frequency-invariant beamforming with concentric circular arrays are used in many applications, including microphone arrays and audio communication. However, existing methods focus on the azimuth-beamwidth and consider uniformly spaced circular arrays. This paper presents an approach to designing a constant elevation-beamwidth beamformer for nonuniform concentric ring arrays. The suggested beamformer aims to maximize the array directivity factor while maintaining fixed beamwidth over a wide range of frequencies. The introduced methodology simultaneously selects the ring placements and designs the beamformer weights that achieve optimal performance. We present the problem constraints and cost function, resulting in a sparse beamformer design. In addition, a uniformly spaced beamformer is incorporated into the optimization cost function to attain improved performance. Time-domain implementation of the ideal beamformer is also presented in this work. Furthermore, in the proposed array configuration, all sensors on each ring share the same weight value. Thus, the computational complexity and the physical hardware required in a physical setup are significantly reduced. Experimental results demonstrate the advantages of the nonuniform beamformer compared to a uniform beamformer in terms of directivity index, white noise gain, and sidelobe attenuation. Avital Kleiman, Israel Cohen, Baruch Berdugo |
IEEE ACM Trans. Audio Speech Lang. Process. | 1 |