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Current fluctuations play an important role in non-equilibrium statistical mechanics, and are a key object of interest in both theoretical studies and in practical applications. So far, most of the studies were devoted to the fluctuations…

Statistical Mechanics · Physics 2021-06-01 Bertrand Lacroix-A-Chez-Toine , Oren Raz

Inferring dynamical models from low-resolution temporal data continues to be a significant challenge in biophysics, especially within transcriptomics, where separating molecular programs from noise remains an important open problem. We…

Machine Learning · Computer Science 2023-10-05 Victor Chardès , Suryanarayana Maddu , Michael J. Shelley

By exploiting a causality property of the nonlinear Fourier transform, a novel decision-feedback detection strategy for nonlinear frequency-division multiplexing (NFDM) systems is introduced. The performance of the proposed strategy is…

Information Theory · Computer Science 2018-04-30 Stella Civelli , Enrico Forestieri , Marco Secondini

The analysis of the time-frequency content of a signal is a classical problem in signal processing, with a broad number of applications in real life. Many different approaches have been developed over the decades, which provide alternative…

Numerical Analysis · Mathematics 2022-06-02 Antonio Cicone , Wing Suet Li , Haomin Zhou

High penetration of renewable energy sources intensifies frequency fluctuations in multi-area power systems, challenging both stability and operational safety. This paper proposes a novel distributed frequency control method that ensures…

Systems and Control · Electrical Eng. & Systems 2025-09-10 Xiemin Mo , Tao Liu

A signal processing method designed for the detection of linear (coherent) behaviors among random fluctuations is presented. It is dedicated to the study of data recorded from nonlinear physical systems. More precisely the method is suited…

Chaotic Dynamics · Physics 2013-10-03 F. Briolle , B. Ricaud , X. Leoncini

A method is presented for investigating the periodic signal content of time series in which a number of signals is present, such as arising from the observation of multiperiodic oscillating stars in observational asteroseismology. Standard…

Astrophysics · Physics 2007-05-23 Frank P. Pijpers

It is by now established that, remarkably, the addition of noise to a nonlinear system may sometimes facilitate, rather than hamper the detection of weak signals. This phenomenon, usually referred to as stochastic resonance, was originally…

Condensed Matter · Physics 2009-10-31 Redouane Fakir

This paper presents a novel approach for estimating the modes of an observed non-stationary mixture signal. A link is first established between the short-time Fourier transform and the sparse sampling theory, where the observations are…

Numerical Analysis · Mathematics 2022-12-23 Quentin Legros , Dominique Fourer

Low-frequency oscillations (LFOs) present a significant challenge to the stability and reliability of power systems, especially in grids with a high penetration of renewable energy sources. Traditional grid-following (GFL) inverters have…

Systems and Control · Electrical Eng. & Systems 2025-06-02 Tamojit Chakraborty , Anamitra Pal , Sam Maleki

The model of a non-autonomous memristor-based oscillator with a line of equilibria is studied. A numerical simulation of the system driven by a periodical force is combined with a theoretical analysis by means of the quasi-harmonic…

Adaptation and Self-Organizing Systems · Physics 2020-10-28 Ivan A. Korneev , Andrei V. Slepnev , Vladimir V. Semenov , Tatiana Vadivasova

We consider detecting the evolutionary oscillatory pattern of a signal when it is contaminated by non-stationary noises with complexly time-varying data generating mechanism. A high-dimensional dense progressive periodogram test is proposed…

Methodology · Statistics 2023-07-20 Hau-Tieng Wu , Zhou Zhou

This paper develops an asymptotic expansion technique in momentum space for stochastic filtering. It is shown that Fourier transformation combined with a polynomial-function approximation of the nonlinear terms gives a closed recursive…

Computational Finance · Quantitative Finance 2013-03-26 Masaaki Fujii

The invariance principle, through which the steady-state behavior of nonlinear systems was introduced by Isidori and Byrnes, is leveraged in this article to bring forth a unifying characterization of the frequency response of nonlinear…

Systems and Control · Electrical Eng. & Systems 2026-04-16 Alessio Moreschini , Matteo Scandella

To analyze signals with rapid frequency variations or transient components, the time-reassigned synchrosqueezing transform (TSST) and its variants have been recently proposed. Unlike the traditional synchrosqueezing transform, TSST squeezes…

Signal Processing · Electrical Eng. & Systems 2025-10-08 Shuixin Li , Jiecheng Chen , Qingtang Jiang , Lin Li

In this paper, we propose a novel receiver structure for single-carrier transmission with frequency domain equalization (FDE) that is exposed to power amplifier (PA) nonlinearities. A two-stage approach is adopted, in which linear…

Information Theory · Computer Science 2021-11-12 Murat Babek Salman , Gokhan Muzaffer Guvensen

Battery impedance spectroscopy models are given by fractional order (FO) differential equations. In the discrete-time domain, they give rise to state-space models where the latent process is not Markovian. Parameter estimation for these…

Optimization and Control · Mathematics 2016-01-29 Pierre E. Jacob , S. M. Mahdi Alavi , Adam Mahdi , Stephen J. Payne , David A. Howey

Time series foundation models (TSFMs) are widely used as generic feature extractors, yet the notion of non-stationarity in their embedding spaces remains poorly understood. Recent work often conflates non-stationarity with distribution…

Machine Learning · Computer Science 2026-04-21 Jinmyeong Choi , Brad Shook , Artur Dubrawski

In this manuscript, we show how flow equation methods can be used to study localisation in disordered quantum systems, and particularly how to use this approach to obtain the non-equilibrium dynamical evolution of observables. We review the…

Disordered Systems and Neural Networks · Physics 2020-02-27 S. J. Thomson , M. Schiró

Fourier transform methods are used to analyze functions and data sets to provide frequencies, amplitudes, and phases of underlying oscillatory components. Fast Fourier transform (FFT) methods offer speed advantages over evaluation of…

Data Analysis, Statistics and Probability · Physics 2015-07-08 Elya Courtney , Michael Courtney