Results 31 to 40 of about 204,835 (237)

Limit theorems, scaling of moments and intermittency for integrated finite variance supOU processes [PDF]

open access: yes, 2019
Superpositions of Ornstein-Uhlenbeck type (supOU) processes provide a rich class of stationary stochastic processes for which the marginal distribution and the dependence structure may be modeled independently.
Grahovac, Danijel   +2 more
core   +4 more sources

Summing Modulo 2 of Stationary Binary Stochastic Processes

open access: yesIEEE Access
In the paper, we analyze the properties of the stochastic process obtained as the result of summing modulo 2 without carry of a finite number of stationary binary stochastic processes, some of which do not satisfy the independence condition.
Mieczyslaw Jessa, Jakub Nikonowicz
doaj   +1 more source

Functional Limit Theorems for Toeplitz Quadratic Functionals of Continuous time Gaussian Stationary Processes [PDF]

open access: yes, 2015
\noindent The paper establishes weak convergence in $C[0,1]$ of normalized stochastic processes, generated by Toeplitz type quadratic functionals of a continuous time Gaussian stationary process, exhibiting long-range dependence.
Bai, Shuyang   +2 more
core   +1 more source

Universal Kriging Prediction of nonstationary Spatial Stochastic Process [PDF]

open access: yesالمجلة العراقية للعلوم الاحصائية, 2010
Spatial Stochastic processes are often divided into two types that are stationary spatial stochastic processes and other nonstationary. In most practical applications the processes are nonstationary .Prediction of these processes are performed by ...
doaj   +1 more source

Multi‐Scale Interface Engineering of MXenes for Multifunctional Sensory Systems

open access: yesAdvanced Functional Materials, EarlyView.
MXenes, as two‐dimensional transition metal carbides and nitrides, demonstrate remarkable capabilities for multifunctional sensing applications. This review systematically examines multi‐scale interface engineering approaches that enhance sensing performance, enable diverse detection functionalities, and improve system‐level compatibility in MXene ...
Jiaying Liao, Sin‐Yi Pang, Jianhua Hao
wiley   +1 more source

A generalized white noise space approach to stochastic integration for a class of Gaussian stationary increment processes [PDF]

open access: yesOpuscula Mathematica, 2013
Given a Gaussian stationary increment processes, we show that a Skorokhod-Hitsuda stochastic integral with respect to this process, which obeys the Wick-Itô calculus rules, can be naturally defined using ideas taken from Hida's white noise space theory ...
Daniel Alpay, Alon Kipnis
doaj   +1 more source

All‐Optical Reconfigurable Physical Unclonable Function for Sustainable Security

open access: yesAdvanced Materials, EarlyView.
An all‐optical reconfigurable physical unclonable function (PUF) is demonstrated using plasmonic coupling–induced sintering of optically trapped gold nanoparticles, where Brownian motion serves as a robust entropy source. The resulting optical PUF exhibits high encoding density, strong resistance to modeling attacks, and practical authentication ...
Jang‐Kyun Kwak   +4 more
wiley   +1 more source

Equilibration of multitime quantum processes in finite time intervals

open access: yesSciPost Physics Core, 2023
A generic non-integrable (unitary) out-of-equilibrium quantum process, when interrogated across many times, is shown to yield the same statistics as an (non-unitary) equilibrated process. In particular, using the tools of quantum stochastic processes, we
Neil Dowling, Pedro Figueroa-Romero, Felix A. Pollock, Philipp Strasberg, Kavan Modi
doaj   +1 more source

Time to reach the maximum for a stationary stochastic process

open access: yesPhysical Review E, 2022
57 pages, 19 figures.
Mori, Francesco   +2 more
openaire   +4 more sources

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

open access: yesAdvanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue   +8 more
wiley   +1 more source

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