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Related papers: The Bispectrum and Its Relationship to Phase-Ampli…

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We make the first attempt to estimate and interpret the biphase data for astronomical time series. The biphase is the phase of the bispectrum, which is the Fourier domain equivalent of the three-point correlation function. The bispectrum…

High Energy Astrophysical Phenomena · Physics 2015-06-16 Thomas J. Maccarone

We present the implementation of a fast estimator for the full dark matter bispectrum of a three-dimensional particle distribution relying on a separable modal expansion of the bispectrum. The computational cost of accurate bispectrum…

Cosmology and Nongalactic Astrophysics · Physics 2014-02-04 M. M. Schmittfull , D. M. Regan , E. P. S. Shellard

Statistics derived from the eigenvalues of sample covariance matrices are called spectral statistics, and they play a central role in multivariate testing. Although bootstrap methods are an established approach to approximating the laws of…

Methodology · Statistics 2019-02-21 Miles Lopes , Andrew Blandino , Alexander Aue

We develop a new formalism for the component separation method Spectral Matching Independent Component Analysis (SMICA) in order to include the information contained in the foregrounds beyond second-order statistics. We also develop a…

Cosmology and Nongalactic Astrophysics · Physics 2026-05-19 M. Citran , H. V. Tran , G. Patanchon , B. van Tent

We consider the problem of estimating a signal from noisy circularly-translated versions of itself, called multireference alignment (MRA). One natural approach to MRA could be to estimate the shifts of the observations first, and infer the…

Information Theory · Computer Science 2018-02-14 Tamir Bendory , Nicolas Boumal , Chao Ma , Zhizhen Zhao , Amit Singer

The ordinary spectrum is restricted in its applications, since it is based on the second order moments (auto and cross-covariances). Alternative approaches to spectrum analysis have been investigated based on other measures of dependence.…

Methodology · Statistics 2022-12-26 Lars Arne Jordanger , Dag Tjøstheim

We present a Bayesian perspective on quantifying the uncertainty of graph signals estimated or reconstructed from imperfect observations. We show that many conventional methods of graph signal estimation, reconstruction and imputation, can…

Signal Processing · Electrical Eng. & Systems 2025-05-22 Lennard Rompelberg , Michael T. Schaub

We present examples of non-Gaussian statistics that can induce bispectra matching local and non-local (including equilateral) templates in biased sub-volumes. We find cases where the biasing from coupling to long wavelength modes affects…

Cosmology and Nongalactic Astrophysics · Physics 2015-04-16 Bekir Baytaş , Aruna Kesavan , Elliot Nelson , Sohyun Park , Sarah Shandera

We study how to probe bispectra of stochastic gravitational waves with pulsar timing arrays. The bispectrum is a key to probe the origin of stochastic gravitational waves. In particular, the shape of the bispectrum carries valuable…

General Relativity and Quantum Cosmology · Physics 2019-03-25 Makoto Tsuneto , Asuka Ito , Toshifumi Noumi , Jiro Soda

The influence of large-scale density fluctuations on structure formation on small scales is described by the three-point correlation function (bispectrum) in the so-called "squeezed configurations," in which one wavenumber, say $k_3$, is…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-19 Chi-Ting Chiang , Christian Wagner , Fabian Schmidt , Eiichiro Komatsu

Various hand-crafted features representations of bio-signals rely primarily on the amplitude or power of the signal in specific frequency bands. The phase component is often discarded as it is more sample specific, and thus more sensitive…

Machine Learning · Computer Science 2020-10-19 Abdelhak Lemkhenter , Paolo Favaro

Understanding the oscillating behaviors that govern organisms' internal biological processes requires interdisciplinary efforts combining both biological and computer experiments, as the latter can complement the former by simulating…

Applications · Statistics 2024-12-17 Youngdeok Hwang , Hang J. Kim , Won Chang , Christian Hong , Steven N. MacEachern

Spectrograms visualize the frequency components of a given signal which may be an audio signal or even a time-series signal. Audio signals have higher sampling rate and high variability of frequency with time. Spectrograms can capture such…

Signal Processing · Electrical Eng. & Systems 2021-09-06 Sidharth Srivatsav Sribhashyam , Md Sirajus Salekin , Dmitry Goldgof , Ghada Zamzmi , Mark Last , Yu Sun

Brain function as measured by multichannel EEG recordings can be described to a high level of accuracy by microstates, characterized as a sequence of time intervals within which the sign invariant normalized scalp electric potential field…

Neurons and Cognition · Quantitative Biology 2022-08-08 Roberto D. Pascual-Marqui , Kieko Kochi , Toshihiko Kinoshita

We investigate the broadband turbulent dynamics of attached and separated flows over a Gaussian bump, focusing on the origin of low-frequency coherent structures. The analysis combines time-resolved experimental measurements with…

Objective: The detection of epileptic seizures from scalp electroencephalogram (EEG) signals can facilitate early diagnosis and treatment. Previous studies suggested that the Gaussianity of EEG distributions changes depending on the…

Signal Processing · Electrical Eng. & Systems 2021-03-03 Akira Furui , Ryota Onishi , Akihito Takeuchi , Tomoyuki Akiyama , Toshio Tsuji

PAC-Bayesian algorithms and Gibbs posteriors are gaining popularity due to their robustness against model misspecification even when Bayesian inference is inconsistent. The PAC-Bayesian alpha-posterior is a generalization of the standard…

Machine Learning · Computer Science 2020-04-23 Lucie Perrotta

Nonlinear spectroscopy is widely used to study the transient dynamics of molecules under strong light-matter coupling, though it remains unclear to what extent uncoupled intracavity molecules obscure signals from the strongly-coupled…

Chemical Physics · Physics 2026-04-08 Alexander M. McKillop , Marissa L. Weichman

In audio signal processing, probabilistic time-frequency models have many benefits over their non-probabilistic counterparts. They adapt to the incoming signal, quantify uncertainty, and measure correlation between the signal's amplitude…

Signal Processing · Electrical Eng. & Systems 2019-02-13 William J. Wilkinson , Michael Riis Andersen , Joshua D. Reiss , Dan Stowell , Arno Solin

Simultaneous electrocardiography (ECG) and phonocardiogram (PCG) provide a comprehensive, multimodal perspective on cardiac function by capturing the heart's electrical and mechanical activities, respectively. However, the distinct and…

Machine Learning · Computer Science 2025-06-13 Sajjad Karimi , Amit J. Shah , Gari D. Clifford , Reza Sameni