20 citations · 33 across the 6 of their papers we have counts for
8 papers
Frame bounds and bandwidth tiling for time-causal bandpass wavelets
Jens E. Pedersen, Tony Lindeberg, Peter Gerstoft
Wavelets and frames that provide strong guarantees for signal representations are a cornerstone in signal processing theory, but have long been restricted to non-causal settings. R…
Dynamic Mode Decomposition by Tensor Evolution for Source Depth
Wenqian Wu, Xiaohong Yang, Guangying Zheng +2
Depth estimation of shallow acoustic sources using a deep-ocean near-bottom vertical line array relies on depth-sensitive interference, which appears as an oscillatory structure in…
Encoding and Decoding Temporal Signals with Spiking Bandpass Wavelets
Jens Egholm Pedersen, Tony Lindeberg, Peter Gerstoft
Spike-based encodings are sparse and energy-efficient. However, previous theory for such spiking representations is largely disconnected from most signal processing literature and…
Scale-covariant spiking wavelets
Jens Egholm Pedersen, Tony Lindeberg, Peter Gerstoft
We establish a theoretical connection between wavelet transforms and spiking neural networks through scale-space theory. We rely on the scale-covariant guarantees in the leaky inte…
Differentiable physics for sound field reconstruction
Samuel A. Verburg, Efren Fernandez-Grande, Peter Gerstoft
Sound field reconstruction involves estimating sound fields from a limited number of spatially distributed observations. This work introduces a differentiable physics approach for…
Machine Learning in Acoustics: A Review and Open-Source Repository
Ryan A. McCarthy, You Zhang, Samuel A. Verburg +2
Acoustic data provide scientific and engineering insights in fields ranging from bioacoustics and communications to ocean and earth sciences. In this review, we survey recent advan…
Distributed acoustic sensing for ocean applications
Angeliki Xenaki, Peter Gerstoft, Ethan Williams +1
Extensive monitoring of acoustic activities is important for many fields, including biology, security, oceanography, and Earth science. Distributed acoustic sensing (DAS) is an evo…
Efficient Sound Field Reconstruction with Conditional Invertible Neural Networks
Xenofon Karakonstantis, Efren Fernandez-Grande, Peter Gerstoft
In this study, we introduce a method for estimating sound fields in reverberant environments using a conditional invertible neural network (CINN). Sound field reconstruction can be…