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Recent work suggests unstable recurrent solutions of the equations governing fluid flow can play an important role in structuring the dynamics of turbulence. Here we present a method for detecting intervals of time where turbulence…

Earthquakes can be detected by matching spatial patterns or phase properties from 1-D seismic waves. Current earthquake detection methods, such as waveform correlation and template matching, have difficulty detecting anomalous earthquakes…

Geophysics · Physics 2019-01-30 Zheng Zhou , Youzuo Lin , Zhongping Zhang , Yue Wu , Paul Johnson

In parameter space of nonlinear dynamical systems, windows of periodic states are aligned following routes of period-adding configuring periodic window sequences. In state space of driven nonlinear oscillators, we determine the torsion…

Pattern Formation and Solitons · Physics 2015-06-11 E. S. Medeiros , R. O. Medrano-T , I. L. Caldas , S. L. T. De Souza

Time series forecasting is often fundamental to scientific and engineering problems and enables decision making. With ever increasing data set sizes, a trivial solution to scale up predictions is to assume independence between interacting…

Machine Learning · Computer Science 2021-01-18 Kashif Rasul , Abdul-Saboor Sheikh , Ingmar Schuster , Urs Bergmann , Roland Vollgraf

Distributed Acoustic Sensing (DAS) is becoming increasingly popular in microseismic monitoring operations. This data acquisition technology converts fiber-optic cables into dense arrays of seismic sensors that can sample the seismic…

Dynamic conditional correlation (DCC) is a method that estimates the correlation between two time series across time. Although used primarily in finance so far, DCC has been proposed recently as a model-based estimation method for…

Applications · Statistics 2020-06-05 Aparna John , Toshikazu Ikuta , Janina D Ferbinteanu , Majnu John

Time series defined by a p-adic pseudo-differential equation is investigated using the expansion of the time series over p-adic wavelets. Quadratic correlation function is computed. This correlation function shows a degree--like behavior…

Mathematical Physics · Physics 2014-04-29 A. Yu. Khrennikov , S. V. Kozyrev , K. Oleschko , A. G. Jaramillo , M. de Jesus Correa Lopez

We introduce a new version of dynamic time warping for samples of observed event times that are modeled as time-warped intensity processes. Our approach is devel- oped within a framework where for each experimental unit or subject in a…

Methodology · Statistics 2012-11-07 Ana Arribas-Gil , Hans-Georg Müller

This study proposes a response-based parameter for strong motion duration which is computed for structures and is the total time they are nonlinear during an earthquake. Correlation between structural response and duration for structures,…

We propose an adaptive control strategy for the simultaneous estimation of topology and synchronization in complex dynamical networks with unknown, time-varying topology. Our approach transforms the problem of time-varying topology…

Multiagent Systems · Computer Science 2024-09-16 Nana Wang , Esteban Restrepo , Dimos V. Dimarogonas

In this paper, for the purpose of data centre energy consumption monitoring and analysis, we propose to detect the running programs in a server by classifying the observed power consumption series. Time series classification problem has…

Neural and Evolutionary Computing · Computer Science 2017-06-08 Yuanlong Li , Han Hu , Yonggang Wen , Jun Zhang

Dynamical systems describe how a physical system evolves over time. Physical processes can evolve faster or slower in different environmental conditions. We use time-warping as rescaling the time in a model of a physical system. This thesis…

Machine Learning · Computer Science 2026-05-12 Jonathon Hirschi

Previous studies showed that hydro-climate processes are stochastic and complex systems, and it is difficult to discover the hidden patterns in the all non-stationary data and thoroughly understand the hydro-climate relationships. For the…

Applications · Statistics 2018-10-02 Jianhua Xu

Multi-channel Analysis of Surface Waves (MASW) is a seismic method employed to obtain useful information about shear-wave velocities in the near surface. A fundamental step in this methodology is the extraction of dispersion curves from…

Starting from the traditional definition of auto-correlation function we can introduce a new quantity, based on the wavelet formalism, called local wavelet auto-correlation function, which contains more information about the correlation…

Astrophysics · Physics 2007-05-23 Stefano Sello

The advent of machine learning (ML) and computer vision has significantly accelerated seismic inversion workflows by reducing the computational cost of traditionally expensive iterative methods. However, the development and evaluation of ML…

Machine Learning · Computer Science 2026-05-21 Ipsita Bhar , Huseyin Tuna Erdinc , Thales Souza , Charles Jones , Felix J. Herrmann

Seismic wavefields recorded on land are strongly distorted by near-surface heterogeneity, introducing trace-specific, frequency-dependent phase perturbations that persist even after advanced time processing. Conventional surface-consistent…

Geophysics · Physics 2026-03-06 Akshika Rohatgi , Andrey Bakulin , Sergey Fomel

For the computational prediction of core electron binding energies in solids, two distinct kinds of modelling strategies have been pursued: the $\Delta$-Self-Consistent-Field method based on density functional theory (DFT), and the GW…

Materials Science · Physics 2023-06-12 Juhan Matthias Kahk , Johannes Lischner

Seismic signals are typically compared using travel time difference or $L_2$ difference. We propose the Wasserstein metric as an alternative measure of fidelity or misfit in seismology. It exhibits properties from both of the traditional…

Mathematical Physics · Physics 2013-11-20 Bjorn Engquist , Brittany D. Froese

Dynamic analysis of structures subjected to earthquake excitation is a time-consuming process, particularly in the case of extremely small time step required, or in the presence of high geometric and material nonlinearity. Performing…

Machine Learning · Computer Science 2021-11-30 Xiao Pan , Zhizhao Wen , T. Y. Yang