XK
Danish Sound Cluster project: Physics-informed Neural Networks for Sound Field Reconstruction
Published on by Xenofon Karakonstantis
The objective of this project is to develop a methodology to predict the sound field in a room, based on a set of sparse measurements distributed about the room. We plan to explore the use of Physics Informed Neural Networks (PINNs) for the task of reconstructing the sound field, based on a set of sparse measurements. The main outcomes of this project are threefold:
- To curate a data set for the training of neural networks in reverberant environments.
- To examine the predictive potential of PINNs to interpolate and extrapolate acoustic data in fine spatial grids.
- Examine the ability of the network to model the propagation of sound in free-fields, which is relevant for sound radiation and noise control.
Cite items from this project
DataCite
3 Biotech
3D Printing in Medicine
3D Research
3D-Printed Materials and Systems
4OR
AAPG Bulletin
AAPS Open
AAPS PharmSciTech
Abhandlungen aus dem Mathematischen Seminar der Universität Hamburg
ABI Technik (German)
Academic Medicine
Academic Pediatrics
Academic Psychiatry
Academic Questions
Academy of Management Discoveries
Academy of Management Journal
Academy of Management Learning and Education
Academy of Management Perspectives
Academy of Management Proceedings
Academy of Management Review
Funding
Ministry of Education and Research (UFS)
Danish Agency for Higher Education and Science
