2 papers
eess.SP2026
The Neural Echo: A Signal Processing Perspective for Understanding Neural Networks
Chongbiao Wang, Daniel Gaa, Joachim Weickert +1
We introduce the neural echo as a tool for understanding the behavior of neural networks. It generalizes the model-based concepts of impulse responses, diffusion echoes, and filter…
cs.SD2026
Phase-Retrieval-Based Physics-Informed Neural Networks For Acoustic Magnitude Field Reconstruction
Karl Schrader, Shoichi Koyama, Tomohiko Nakamura +1
We propose a method for estimating the magnitude distribution of an acoustic field from spatially sparse magnitude measurements. Such a method is useful when phase measurements are…