Acoustic field visualization and source localization via physics-informed learning of sparse data with adaptive sampling
Traditional methods for acoustic field visualization require considerable effort for capturing large amounts of acoustic data to achieve a high resolution field map, highly limiting their widespread use. In this study, we propose an approach for acoustic field visualization based on physics-informed...
Saved in:
| Main Authors: | Jian Chen, Dan Xu, Weijian Fang, Shiwei Wu, Haiteng Wu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2024-11-01
|
| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0227921 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Mixed Far-Field and Near-Field Source Localization Algorithm via Sparse Subarrays
by: Jiaqi Song, et al.
Published: (2018-01-01) -
Evaluation of Sparse Acoustic Array Geometries for the Application in Indoor Localization
by: Georg K.J. Fischer, et al.
Published: (2024-01-01) -
Localization of Near-Field Sources Based on Sparse Signal Reconstruction with Regularization Parameter Selection
by: Shuang Li, et al.
Published: (2017-01-01) -
Localisation and classification of mixed far‐field and near‐field sources with sparse reconstruction
by: Meidong Kuang, et al.
Published: (2022-06-01) -
Robust and sparse estimator for EEG source localization
by: Teja Mannepalli, et al.
Published: (2025-06-01)