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We investigate the reconstruction of the transmission matrix of a time-evolving atmospheric channel with an online recursive optimization routine, using wave-optics simulations. We demonstrate that this estimation technique is able to keep…

Optics · Physics 2025-04-02 Giacomo Sorelli , Douglas McDonald , Szymon Gladysz

This paper concerns the reconstruction of the scattering coefficient in a two-dimensional transport equation from angularly averaged measurements when the probing source is isotropic and time-harmonic. This is a practical setting in the…

Analysis of PDEs · Mathematics 2011-10-17 Guillaume Bal , Francois Monard

This report shows formulation of wave scattering in frequency domain. The formulation provides an understanding of S-matrix solver which is named as Scattering Matrix Analyzer (SMatrAn). The S-matrix has the whole of amplitude and phase…

Computational Physics · Physics 2021-04-15 Tatsuya Usuki

Thanks to the latest advancements in wavefront shaping, optical methods have proven crucial to achieve imaging and control light in multiply scattering media, like biological tissues. However, the stability times of living biological…

Optics · Physics 2023-09-21 Lorenzo Valzania , Sylvain Gigan

The Continuous Boostlet Transform (CBT) is introduced as a powerful tool for analyzing spatiotemporal signals, particularly acoustic wavefields. Overcoming the limitations of classical wavelets, the CBT leverages the Poincar\'e group and…

Signal Processing · Electrical Eng. & Systems 2025-11-04 Owais Ahmad , Jasifa Fayaz

It is shown that any convolution operator in the time domain can be represented exactly as a multiplication operator in the time-scale (wavelet) domain. The Mellin transform gives a one-to-one correspondence between frequency filters…

Mathematical Physics · Physics 2007-05-23 Gerald Kaiser

Transformers have drawn attention in the MIR field for their remarkable performance shown in natural language processing and computer vision. However, prior works in the audio processing domain mostly use Transformer as a temporal feature…

Sound · Computer Science 2021-10-26 Wei-Tsung Lu , Ju-Chiang Wang , Minz Won , Keunwoo Choi , Xuchen Song

We present a novel approach to the regression of quantum mechanical energies based on a scattering transform of an intermediate electron density representation. A scattering transform is a deep convolution network computed with a cascade of…

Machine Learning · Computer Science 2016-05-23 Matthew Hirn , Nicolas Poilvert , Stéphane Mallat

The nonlinear Fourier transform, which is also known as the forward scattering transform, decomposes a periodic signal into nonlinearly interacting waves. In contrast to the common Fourier transform, these waves no longer have to be…

Information Theory · Computer Science 2015-11-24 Sander Wahls , H. Vincent Poor

Consider the inverse scattering of time-harmonic acoustic scattering by an infinite rough surface which is supposed to be a local perturbation of a plane. A novel version of reverse time migration (RTM) is proposed to reconstruct the shape…

Analysis of PDEs · Mathematics 2023-10-24 Jianliang Li , Hao Wu , Jiaqing Yang

Time-frequency representations of audio signals often resemble texture images. This paper derives a simple audio classification algorithm based on treating sound spectrograms as texture images. The algorithm is inspired by an earlier visual…

Computer Vision and Pattern Recognition · Computer Science 2008-09-29 Guoshen Yu , Jean-Jacques Slotine

Human auditory perception is compositional in nature -- we identify auditory streams from auditory scenes with multiple sound events. However, such auditory scenes are typically represented using clip-level representations that do not…

Sound · Computer Science 2025-03-04 Sripathi Sridhar , Mark Cartwright

Structured illumination enables the tailoring of an imaging device's optical transfer function to enhance resolution. We propose the incorporation of a temporal periodic modulation, specifically a rotating mask, to encode multiple transfer…

Optics · Physics 2023-06-27 Guillaume Noetinger , Fabrice Lemoult , Sébastien M. Popoff

Path loss prediction is a beneficial tool for efficient use of the radio frequency spectrum. Building on prior research on high-resolution map-based path loss models, this paper studies convolutional neural network input representations in…

Machine Learning · Computer Science 2026-02-05 Ryan G. Dempsey , Jonathan Ethier , Halim Yanikomeroglu

An acoustic reverberator consisting of a network of delay lines connected via scattering junctions is proposed. All parameters of the reverberator are derived from physical properties of the enclosure it simulates. It allows for simulation…

Sound · Computer Science 2015-07-10 Enzo De Sena , Huseyin Hacihabiboglu , Zoran Cvetkovic , Julius O. Smith

Patient-independent detection of epileptic activities based on visual spectral representation of continuous EEG (cEEG) has been widely used for diagnosing epilepsy. However, precise detection remains a considerable challenge due to subtle…

Signal Processing · Electrical Eng. & Systems 2023-05-01 Ruizhe Zheng , Jun Li , Yi Wang , Tian Luo , Yuguo Yu

We extend the T-matrix approach to light scattering by spherical particles to some simple cases in which the scatterers are optically anisotropic. Specifically we consider cases in which the spherical particles include radially and…

Optics · Physics 2009-11-07 A. D. Kiselev , V. Yu Reshetnyak , T. J. Sluckin

The famous question of Mark Kac "Can one hear the shape of a drum?" addressing the unique connection between the shape of a planar region and the spectrum of the corresponding Laplace operator can be legitimately extended to scattering…

Quantum Physics · Physics 2012-07-27 Oleh Hul , Michał Ławniczak , Szymon Bauch , Adam Sawicki , Marek Kuś , Leszek Sirko

Convolutional neural networks (CNNs) constructed natively on the sphere have been developed recently and shown to be highly effective for the analysis of spherical data. While an efficient framework has been formulated, spherical CNNs are…

Computer Vision and Pattern Recognition · Computer Science 2022-01-25 Jason D. McEwen , Christopher G. R. Wallis , Augustine N. Mavor-Parker

This paper describes a method for decomposing steady-state instrument data into excitation and formant filter components. The input data, taken from several series of recordings of acoustical instruments is analyzed in the frequency domain,…

Sound · Computer Science 2007-05-23 Ilia Bisnovatyi , Michael J. O'Donnell