1 citations · 1 across the 5 of their papers we have counts for
6 papers
Towards Physics-Informed Neural Networks for Stiff Guitar String Vibrations
Xinmeng Luan, Kensuke Okada, Ryoya Tabata +1
Modeling stiff string vibrations is challenging due to their dispersive and high-frequency characteristics. This study investigates the effectiveness of Physics-Informed Neural Net…
Inverse Problems in Musical Instrument Modeling: A Structured Taxonomy and Review
Xinmeng Luan, Gary Scavone
Inverse problems arise in a wide range of applications in musical acoustics, including physics-based sound synthesis, musical instrument modeling, design, and optimization. However…
Masked Wavelet Scattering Transform Neural Field for Sound Field Reconstruction
Xinmeng Luan, Samuel A. Verburg, Efren Fernandez-Grande +1
In this paper, we propose a reconstruction framework that leverages the Wavelet Scattering Transform (WST) as a multi-scale feature extractor to impose statistical priors under spa…
Physics-Informed Deep Learning for Nonlinear Friction Model of Bow-string Interaction
Xinmeng Luan, Gary Scavone
This study investigates the use of an unsupervised, physics-informed deep learning framework to model a one-degree-of-freedom mass-spring system subjected to a nonlinear friction b…
Acoustic Field Reconstruction in Tubes via Physics-Informed Neural Networks
Xinmeng Luan, Kazuya Yokota, Gary Scavone
This study investigates the application of Physics-Informed Neural Networks (PINNs) to inverse problems in acoustic tube analysis, focusing on reconstructing acoustic fields from n…
Acoustic Characterization of the Resonator in the Chinese Transverse Flute (dizi)
Xinmeng Luan, Song Wang, Gary Scavone +1
The dizi is a traditional Chinese transverse flute and is most distinguished from the western flute by the presence of a hole covered by a wrinkled membrane. In this study, we anal…