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Related papers: Self-Excited Multifractal Dynamics

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We propose a new class of waveform foundation models that departs from conventional sequence based representations by modeling physiological time series as realizations of latent event processes. Rather than treating signals as collections…

Machine Learning · Computer Science 2026-05-12 Li Na , Yuanyun Zhang , Shi Li

A new approach to the problem of finding the asymptotical behaviour of large orders of semiclassical expansion is suggested. Asymptotics of high orders not only for eigenvalues, but also for eigenfunctions, are constructed. Thus, one can…

Quantum Physics · Physics 2009-09-25 O. Yu. Shvedov

We study magnetogenesis in axionlike inflation driven by a pseudoscalar field $\phi$ coupled axially to the electromagnetic (EM) field $(\beta/M_{p})\phi F_{\mu\nu}\tilde{F}^{\mu\nu}$ with dimensionless coupling constant $\beta$. A set of…

Cosmology and Nongalactic Astrophysics · Physics 2019-09-20 O. O. Sobol , E. V. Gorbar , S. I. Vilchinskii

Modern x-ray free-electron lasers (XFELs) produce x-ray pulses of exceptional transverse coherence. This is due largely to the process of optical guiding by which the radiation is both refractively guided by the bunched electron beam and…

Accelerator Physics · Physics 2021-04-20 River R. Robles , Gabriel Marcus , Zhirong Huang

The characteristic feature of semi-selfsimilar process is the invariance of its finite dimensional distributions by certain dilation for specific scaling factor. Estimating the scale parameter $\lambda$ and the Hurst index of such processes…

Statistics Theory · Mathematics 2012-07-11 Saeid Rezakhah , Anne Philippe , Navideh Modarresi

Spatially confined rigid membranes reorganize their morphology in response to the imposed constraints. A crumpled elastic sheet presents a complex pattern of random folds focusing the deformation energy while compressing a membrane resting…

Telemetry streams from large-scale Internet-connected systems (e.g., IoT deployments and online platforms) naturally form an irregular multivariate time series (IMTS) whose accurate forecasting is operationally vital. A closer examination…

Machine Learning · Computer Science 2026-02-04 Ziyu Zhou , Yuchen Fang , Weilin Ruan , Shiyu Wang , James Kwok , Yuxuan Liang

The brain can reproduce memories from partial data; this ability is critical for memory recall. The process of memory recall has been studied using auto-associative networks such as the Hopfield model. This kind of model reliably converges…

Neurons and Cognition · Quantitative Biology 2016-05-18 James P. Roach , Leonard M Sander , Michal R. Zochowski

This article proposes a dynamical system modeling approach for the analysis of longitudinal data of self-regulated systems experiencing multiple excitations. The aim of such an approach is to focus on the evolution of a signal (e.g., heart…

A model for fault dynamics consisting of two rough and rigid brownian profiles that slide one over the other is introduced. An earthquake occurs when there is an intersection between the two profiles. The energy release is proportional to…

Condensed Matter · Physics 2019-08-17 V. De Rubeis , R. Hallgass , V. Loreto , G. Paladin , L. Pietronero , P. Tosi

It has recently been found that the evolution of the preparation of a strong earthquake (EQ), as it is monitored through fracture-induced electromagnetic emissions (EME) in the MHz band, presents striking similarity with the evolution of a…

In this work the multifractal analysis of the kinesiological surface electromyographic signal is proposed. The goal was to investigate the level of neuromuscular activation during complex movements on the laparoscopic trainer. The basic…

Data Analysis, Statistics and Probability · Physics 2017-09-27 Paulina Trybek , Michal Nowakowski , Lukasz Machura

This paper extends the existing fractional Hawkes process to better model mainshock-aftershock sequences of earthquakes. The fractional Hawkes process is a self-exciting point process model with temporal decay kernel being a Mittag-Leffler…

Applications · Statistics 2026-04-13 Louis Davis , Boris Baeumer , Ting Wang

SEMMS (Scalable Empirical-Bayes Model for Marker Selection) is a variable-selection procedure for generalized linear models that uses a three-component normal mixture prior on regression coefficients. In its original form, SEMMS assumes…

Computation · Statistics 2026-03-18 Haim Bar , Martin T. Wells

Nonadiabatic effects in chemical reaction at metal surfaces, due to excitation of electron-hole pairs, stand at the frontier of the studies of gas-surface reaction dynamics. However, the first principles description of electronic excitation…

Chemical Physics · Physics 2019-12-20 Yaolong Zhang , Reinhard J. Maurer , Bin Jiang

The quantitative analysis of non-invasive electrophysiology signals from electroencephalography (EEG) and magnetoencephalography (MEG) boils down to the identification of temporal patterns such as evoked responses, transient bursts of…

Signal Processing · Electrical Eng. & Systems 2022-07-12 Cédric Allain , Alexandre Gramfort , Thomas Moreau

Spatially extended systems can support local transient excitations in which just a part of the system is excited. The mechanisms reported so far are local excitability and excitation of a localized structure. Here we introduce an…

Pattern Formation and Solitons · Physics 2017-03-01 P. Parra-Rivas , M. A. Matias , P. Colet , L. Gelens , D. Walgraef , D. Gomila

Fast Incremental Expectation Maximization (FIEM) is a version of the EM framework for large datasets. In this paper, we first recast FIEM and other incremental EM type algorithms in the {\em Stochastic Approximation within EM} framework.…

Machine Learning · Computer Science 2021-01-01 Gersende Fort , P. Gach , E. Moulines

This paper reviews and extends some recent results on the multivariate fractional Brownian motion (mfBm) and its increment process. A characterization of the mfBm through its covariance function is obtained. Similarly, the correlation and…

In Refs. [1,2] we have shown how a combination of modern linear-scaling DFT, together with a subsequent use of large, effective tight-binding Hamiltonians, allows to compute multifractal wave functions yielding the critical properties of…

Disordered Systems and Neural Networks · Physics 2019-02-27 Edoardo G. Carnio , Nicholas D. M. Hine , Rudolf A. Römer
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